Every convex quadrilateral can be regarded as the perspective projection of a unit square (Dörrie, 100 Great Problems of Elementary Mathematics, problem 72). A unit circle inscribed in the unit square projects to an ellipse inscribed in the quadrilateral. This ellipse can be drawn, and its parameters calculated, without reference to any particular configuration of the unit circle, the viewpoint, and the plane of projection. The ellipse is completely determined by the coordinates of the vertices of the quadrilateral.
It easy to find by construction the points where the ellipse touches the quadrilateral. The image of the centre of the unit circle is at the intersection of the diagonals. Opposite sides of the quadrilateral meet in two "vanishing points". A line from each vanishing point through the intersection of the diagonals intersects the quadrilateral at the points of tangency.
The centre of the ellipse can be found by another construction. Bisect the four chords joining the points of tangency. The lines through each mid-point and corresponding vertices of the quadrilateral meet at the centre of the ellipse.
The inclination of the major and minor axes has an inscrutable relationship with the the shape of the quadrilateral. In a figure which may be regarded as representing an array of circular discs, subtle changes of inclination occur between neighbouring ellipses, while tangency at the points of contact is maintained.
Such figures are hard to draw accurately by hand. To draw a circle in perspective, draughtsmen are usually advised to draw an ellipse freehand, tangent to the four points of contact. If the centre is constructed as above, the symmetry of the ellipse can be exploited by rotating the quadrilateral through 180° about the centre to give four additional points of contact.
It is possible to derive a matrix which transforms the unit square by a perspective projection to an arbitrary quadrilateral. The transformation of point p to point q is described by
where ρ is a scale factor (Beardsley, equation 19).
ρ [   ] = T [   ] = [ ] [   ] q0 p0 A B C p0 q1 p1 D E F p1 1 1 G H I 1
The unit square with homogeneous coordinates
is transformed to an arbitrary quadrilateral(-1, 1, 1) ( 1, 1, 1) (-1, -1, 1) ( 1, -1, 1)
by a matrix with these coefficients:-(W0, W1, 1) (X0, X1, 1) (Z0, Z1, 1) (Y0, Y1, 1)
A = X0 Y0 Z1 - W0 Y0 Z1 - X0 Y1 Z0 + W0 Y1 Z0 - W0 X1 Z0 + W1 X0 Z0 + W0 X1 Y0 - W1 X0 Y0 B = W0 Y0 Z1 - W0 X0 Z1 - X0 Y1 Z0 + X1 Y0 Z0 - W1 Y0 Z0 + W1 X0 Z0 + W0 X0 Y1 - W0 X1 Y0 C = X0 Y0 Z1 - W0 X0 Z1 - W0 Y1 Z0 - X1 Y0 Z0 + W1 Y0 Z0 + W0 X1 Z0 + W0 X0 Y1 - W1 X0 Y0 D = X1 Y0 Z1 - W1 Y0 Z1 - W0 X1 Z1 + W1 X0 Z1 - X1 Y1 Z0 + W1 Y1 Z0 + W0 X1 Y1 - W1 X0 Y1 E = -X0 Y1 Z1 + W0 Y1 Z1 + X1 Y0 Z1 - W0 X1 Z1 - W1 Y1 Z0 + W1 X1 Z0 + W1 X0 Y1 - W1 X1 Y0 F = X0 Y1 Z1 - W0 Y1 Z1 + W1 Y0 Z1 - W1 X0 Z1 - X1 Y1 Z0 + W1 X1 Z0 + W0 X1 Y1 - W1 X1 Y0 G = X0 Z1 - W0 Z1 - X1 Z0 + W1 Z0 - X0 Y1 + W0 Y1 + X1 Y0 - W1 Y0 H = Y0 Z1 - X0 Z1 - Y1 Z0 + X1 Z0 + W0 Y1 - W1 Y0 - W0 X1 + W1 X0 I = Y0 Z1 - W0 Z1 - Y1 Z0 + W1 Z0 + X0 Y1 - X1 Y0 + W0 X1 - W1 X0
Given the inverse matrix
the coefficients of the ellipse equation ax2 + 2bxy + cy2 + 2dx + 2fy + g = 0 are
T-1 = [ ] J K L M N O P Q R
a = J2 + M2 - P2
b = JK + MN - PQ
c = K2 + N2 - Q2
d = JL + MO - PR
f = KL + NO - QR
g = L2 + O2 - R2
The centre, angle of rotation, and semi-axis lengths of the ellipse can then be obtained from these coefficients (MathWorld ellipse article, equations 19-23).
Although these formulae allow the ellipse and its axes to be calculated and drawn programmatically, they do not illuminate the underlying geometry. The axes can be determined by some classical constructions (Eagles, problem 81), but the steps are complicated and indirect.
Here is a construction using projective geometry. It is based on a message from José H. Nieto posted to the sci.math newsgroup.
M, N, P, and Q are the points where the ellipse is tangent to the yellow quadrilateral (from the construction described above). Draw the circle through P with tangent m to the quadrilateral at M. This circle is homologous to the ellipse, with M as the centre of homology. Project N and Q on to this circle at N´ and Q´, where MN and MQ, respectively, meet the circle. The green line passing through P and the intersection of lines NQ and N´Q´ is the axis of the homology. The inclination of the ellipse axes is determined by the angle between the homology axis and the tangent m. The red line which bisects this angle is parallel to the major or minor axis of the ellipse.
This construction is interactive, thanks to the JavaSketchpad applet. (Needs Java enabled in browser. Chrome not supported.) Coding of the construction was facilitated by Hans Klein's JSPgenerator authoring tool. The applet dynamically updates the construction when a vertex (red dot) of the quadrilateral is dragged to a new position. Note that the homology axis passes through the the two points where the circle intersects the ellipse. This cannot be used to determine the axis, however, as the ellipse has not been drawn at this stage.
The 'Show' button shows the full construction for the endpoints of the major axis AB and the minor axis CD, which fully determine the shape and position of the ellipse. Let S´ be the point where N´Q´ intersects a parallel to NQ through M. The limit line parallel to the homology axis intersects the tangent m at X´. With centre X´ and radius X´M draw a circle which intersects the limit line at points Y´ and Z´. Let U´ and V´ be the intersections with this circle of the lines from the centre of the original circle to Y´ and Z´, respectively. Let Y´V´ meet the original circle at points A´ and B´, and let Z´U´ meet it at C´ and D´. The homologous projection of points A´, B´, C´, and D´ gives the vertices of the ellipse: A, B, C, and D.
Here is another construction to obtain the ellipse axes, based on Philippe Chevanne's construction (step 2).
Chords NM and MQ are bisected by blue and green lines from corresponding vertices of the quadrilateral. These lines intersect at the centre O of the inscribed ellipse. Blue and green lines at the centre parallel to the chords establish the directions of two pairs of conjugate diameters. They intersect a circle passing through O at four points on the circumference. The blue and green lines joining corresponding points intersect at W. The red line passing through W and the centre of the circle intersects the circumference at two points. The red lines through these two points and the centre of the ellipse are the major and minor axes.


MATH 211 Signature Assignment Name:
- To study about the relationship between height and the weight, you need to collect a sample of
nine (9) people using a systematic sampling method.
a. What is the population of people? Where and how are you going to collect your sample? Does your
sample accurately represent your population? Why or why not?
b. Collect the sample and record the data.
- (CLO 1) Construct a confidence interval to estimate the mean height and the mean weight by
completing the following:
a. Find the sample mean and the sample standard deviation of the height.
b. Find the sample mean and the sample standard deviation of the weight.
c. Construct and interpret a confidence interval to estimate the mean height.
d. Construct and interpret a confidence interval to estimate the mean weight.
- (CLO 2) Test a claim that the mean height of people you know is not equal to 64 inches using
the p-value method or the traditional method by completing the following:
a. State H0 and H1.
b. Find the p value or critical value(s).
c. Draw a conclusion in context of the situation.
- (CLO 3) Create a scatterplot with the height on the x-axis and the weight on the y-axis. Find the
correlation coefficient between the height and the weight. What does the correlation coefficient tell
you about your data? Construct the equation of the regression line and use it to predict the weight of
a person who is 68 inches tall.
- Write a paragraph or two about what you have learned from this process. When you read, see, or
hear a statistic in the future, what skills will you apply to know whether you can trust the result?


Published January 1975
by Addison-Wesley Pub (Sd) .
Written in English
|The Physical Object|
|Number of Pages||131|
Used â€“ Good Condition: A used book in this condition may have cosmetic defects (marks, wears, cuts, bends, crushes) on the cover, spine, pages or dust cover. The pages may include limited notes and highlighting. This item is a retired library book and may include related stickers, labels, stamps, remainder marks, and other markings/5(34). In mathematics, modular arithmetic is a system of arithmetic for integers, where numbers "wrap around" when reaching a certain value, called the modern approach to modular arithmetic was developed by Carl Friedrich Gauss in his book Disquisitiones Arithmeticae, published in A familiar use of modular arithmetic is in the hour clock, in which the . Example: Arithmetic. Here is a module type that represents values that support the usual operations from arithmetic, or more precisely, a field. module type Arith = sig type t val zero: t val one: t val (+): t -> t -> t val (*): t -> t -> t val (~-): t -> t end. I am searching for some good book which section is devoted to modular arithmetic. I am self learner so I strongly prefer that book has exercises best with answers or solutions. I have CS background and has taken course on discrete mathematics but besides some basic facts on modulo operation it lacked some introduction to modular arithmetic.
“As to the need of improvement there can be no question whilst the reign of Euclid continues. My own idea of a useful course is to begin with arithmetic, and then not Euclid but algebra. Next, not Euclid, but practical geometry, solid as well as plane; not demonstration, but to make not Euclid, but elementary vectors, conjoined with algebra, and applied to . This book combines the Elementary Math and the Intermediate Math of the fifth editions into a single volume. The arithmetic topics include whole numbers, fractions, decimals, the percent symbol (%); ratio, proportion, areas, perimeters, scientific notation, and measurements. A good book is from AOPS, or Art of Problem Solving. It’s a series of math books from pre-algebra to olympiad geometry I believe. Written by Richard Ruscyk, the book title is called “Introductory to Number Theory”. Even though you want a modulo ar. 3rd E dition. C opyright!c A nthony W eaver, June , D epartm ent of M athem atics and C om puter S cience, C P H , B ronx C om m unity C ollege, File Size: 2MB.
Modular arithmetic is a system of arithmetic for integers, which considers the remainder. In modular arithmetic, numbers "wrap around" upon reaching a given fixed quantity (this given quantity is known as the modulus) to leave a remainder. Modular arithmetic is often tied to prime numbers, for instance, in Wilson's theorem, Lucas's theorem, and Hensel's lemma, and . Examples: Decimals on the Number Line Example 5 a) Plot on the number line with a black dot. b) Plot with a green dot. Solution: For we split the segment from 0 to 1 on the number line into ten equal pieces between 0 and 1 and then countFile Size: KB. Modular arithmetic is also called clock-arithmetic because we only use 12 numbers to tell standard time. On clocks we start at 1 instead of 0, continue to 12, and then start at 1 again. Hence the name clock-arithmetic. The sequence also continues into what would be the negative numbers. What would have been -1 is now n - 1. For example. Great deals on Mathematics Books Get cozy and expand your home library with a large online selection of books at Fast & Free shipping on many items!


I recently had a conversation with a Lady Friend, and it went a little like this:
TB: What are you studying?
LF: I'm getting a business degree,
TB: So you want to be a secretary?
LF: Very Funny.
TB: I thought so, too.
LF: My dad wanted me to get an engineering degree, but I Don't Like Math.
TB: You mean you don't like being bad at math?
LF: Okay, no, but I'm pretty decent at it
LF: Seriously! I was in honors math in High School!
TB: You might as well be getting a Philosophy or Gender Studies Degree.
LF: Hey, Philosophy is my minor.
TB: I have to go, bye,
my lady friend there needs to change her mindset if she wants to get smarter. I used to say I didn't like math, then I realized that it was just because I did not enjoy practicing skills. So I learned how to practice skills, and then found that mathematics came a lot easier when I wasn't depressed every time I had to start on my homework
P.S. I ended up changing my degree from Pre-Med to Business-Economics.


Talk: Dr. Christoph Hofer-Temmel (November 17, 2015 at 02:00 pm, LNT Library N2405)
On November 17, 2015 at 02:00 pm, Dr. Christoph Hofer-Temmel from NLDA will be giving a talk in the LNT Library N2405 about "Existence and representation problems in discrete stationary processes".
Existence and representation problems in discrete stationary processes
Dr. Christoph Hofer-Temmel
A process is stationary, if its law is invariant under a time shift. Well known examples of stationary processes are iid process, Markov chains, Gibbs ensembles and block-factor constructions. A classic question are the search for necessary and sufficient conditions to represent a general stationary process as simple constructs of the above basic processes. First, I review the problem of lumpability, i.e., representing a stationary process by a deterministic coordinate-wise projection of a Markov chain (this may be seen as a special case of a hidden Markov model). Second, I review recent work by Holroyd et al on one-dependent colorings of the integers, involving factors of Bernoulli. Finally, I turn to one-color marginals and binary one-dependent processes, where stochastic domination enters the game.
Christoph Hofer-Temmel studied mathematics at the TU Graz and Aix-Marseille Université. He defended his PhD about Bernoulli random fields and applications in percolation theory and statistical mechanics in 2012. Afterwards he spent 2 years as a postdoc at the VU Amsterdam and is since 2015 assistant professor at the NLDA in Den Helder. His current research centers around point processes and stochastic domination in the context of percolation and statistical-mechanical models and lumpings and entropy of stochastic processes.


Kathy Morris: Making math fun
By JOELLE BURNETTE / Towns Correspondent
Take progressive creativity, add some exponential training, and multiply with imagination. The sum total is Kathy Morris, a Sonoma State University professor who has come up with a new way to make learning math fun.
“We want every kid to think math is like ice cream,” she said. “We are on the precipice of doing something great in California.”
Morris, 46, is an associate professor in the Department of Literacy, Elementary and Early Education, helping her students learn how to teach mathematics in the elementary grades.
Using a $250,000 grant from the California Postsecondary Education Commission, she also is teaching math educators from five Northern California counties how to implement new federal math standards in their kindergarten through high school classes.
It involves adding applied mathematics to the computational skills that now dominate the curriculum.
Morris is excited by the change that will teach children how to get their heads out of the book and apply math in the real world, better preparing them for college and careers.
“It’s about making sense of your world,” she said. “(Students) will know how math can help them and not just be something to avoid.”
A math enthusiast to the core, Morris finds it upsetting when popular culture pokes fun at the subject. Under the umbrella of the federal No Child Left Behind program, math classes stressed computation rather than thinking about how to use numbers.
She considers that approach a “huge fiasco,” referring to it as “the road to purgatory paved with good intentions.”
The rhetoric behind it — wanting children to succeed — is terrific, she said, but “the ways in which we’ve gone about it have been injurious to children and to teachers. We are now in the world of the $1 calculator, yet we still spend most of our instructional time training children to do what that cheap tool can do.”
Morris points to the recent home mortgage meltdown as an example of how that approach can go wrong. People took out mortgages they couldn’t afford, Morris said, partly because schools didn’t properly teach them how to use math outside the classroom to project income, the impact of adjustable rates and the like.
“We may have taught them to compute, but not when to compute. That’s exactly what our world is demanding,” she said.
By changing the way math is taught, “You start moving into this world of (people) being curious about a situation, driving a desire to figure something out.”
Morris was raised in Marin County and played games with her parents that required her to use mathematics. She credits them with teaching her that math can be fun and creative, not a drudgery.
“I always liked math,” she said. “I was the one with my hand up quick.”
As a child, Morris enjoyed memorizing multiplication tables and carrying out computations. And at Redwood High School she encountered a group of teachers who influenced her future career.
Redwood teachers Lyle Fisher, Bill Medigovich and Roberta Koss were among the “movers and shakers” in the late 1970s and early 1980s, when California’s math education was being reborn.
Koss went on to join the board of the National Council of Teachers of Mathematics and is known for innovative education reforms she instigated.
“It was a time when California was leading the nation,” Morris said. That’s how good the state’s math standards were.
Fisher and Medigovich inspired her with their problem-based approach to mathematics. “It was an amazing transformation from just something that I could do to something that was captivating,” she said.
Reflecting those times, she said, new standards also will include more reasoning and communicating of ideas.
While heading up the grant program to instruct math teachers, Morris also wants the general public to understand the importance of continuous learning for teachers.
Past budget cuts significantly decreased professional development days for teachers, she said, causing the actual teaching of a subject to vary from one classroom or school to the next. As a result, children’s math skills are “all over the map” by the time they reach the fourth grade.
“I firmly believe that professional development leads to better schools, better opportunities for our kids and greater coherence from grade to grade and school to school,” Morris said. “That’s what we’re lacking.”
Using Rohnert Park-Cotati Unified School District as an example, she said, “Teachers haven’t had the time to learn and grow together, coherently. They’re left to their own whim and the wind.”
Her advice to parents is to insist on a “thinking curriculum.” “Insist that students have an opportunity to develop sense-making, perseverance and reasoning,” Morris said.
When children come home from school talking about what they learned in math, ask them how and why that problem works and if there is another way to work it out.


This post gives a beginner their first look into quantum computing. It covers all the basics required to understand how quantum teleportation works. For the teleportation algorithm itself see the second part of this series here, and for how it is implemented using Qiskit on a real quantum computer, see the third part here. For this tutorial I will assume a basic understanding of linear algebra and braket notation. Although I will use braket notation throughout, all of this could also be though of in terms of normal matrix notation too.
As I am sure you are all familiar with, bits on a classical computer can be stores as either a 0 or a 1. What makes quantum computing different is that we can also have a bit that is in a superposition of 0 and 1.
We will define the two possible measurements as the kets |0> and |1>. The |0> state is the state in which we have 100% probability of measuring 0, and the |1> state is the state where we have 100% probability of measuring 1. All other states can then be represented as a linear combination of these.
The coefficients a and b represent the probability amplitudes of measuring each state. So, if we have this state we would have a probability equal to a² of measuring 0 and b² of measuring 1.
This basis of |1> and |0> is the most common in quantum computing. For teleportation we also need to define one other basis out of the infinitely many possibilities. The |+> state and the |-> state are defined as following in terms of the |0>, |1> basis. They are both in an equal superposition, with equal probabilities of ½ of measuring 0 and 1. The difference is solely a phase difference.
In quantum mechanics, when we take a measurement the state collapses onto one of the eigenstates of the system. Therefore for these bases there are two different types of measurement. The first is called a Z measurement and in taking this measurement we collapse the state onto one of the states in the |0> |1> (Z basis). The second is called an X measurement and this collapses the state onto one of the |+> |-> states (X basis).


- Title： Subspace Clustering and Its Development for Manifold-valued Data
- Date：10:00pm US East time, 10/15/2022
- Date：10:00am Beijing time, 10/16/2022
- Zoom ID：933 1613 9423
- Zoom PWD：416262
Speaker: Professor Junbin Gao, The Professor of Big Data Analytics, The University of Sydney Business School, The University of Sydney, NSW 2006 Australia
In this talk I will review my research on the manifold-valued data analysis and its applications in machine learning tasks such as clustering and classification. Particularly I will introduce how the subspace clustering approach is applied to clustering typical manifold-valued data widely seen in computer vision such as Grassmannian manifolds, Stiefel manifold, SPD manifold, and functional data. The topics to be covered include multidimensional data analysis, machine learning algorithm for manifold-valued data, advanced deep learning for multidimensional data, and their potential applications in modern business and economics domains.
Professor Junbin Gao is the Professor of Big Data Analytics in the University of Sydney Business School. Prior to his USyd appointment, he was a Professor in Computing Science in the School of Computing and Mathematics and the deputy Director of Centre for Research in Complex Systems (CRiCS) at Charles Sturt University (CSU). He was a senior lecturer, a lecturer in Computer Science at University of New England, Australia. He was an associate lecturer, lecturer, associate professor and professor in Department of Mathematics at Huazhong University of Science and Technology, prior coming to Australia. Professor Gao obtained his PhD from Dalian University of Technology, China. His main research interests include machine learning, data mining, Bayesian learning and inference, and business analysis. His research is supported by two ARC (Australian Research Council) DP grants and two larger industrial grants. He has published more than 300 research papers in top journals (such as IEEE PAMI, NNLS, IP) and top conferences (CVPR, ICML, AAAI, IJCAI etc). In 2014, his research work on dimensionality reduction was highly featured by The Australian, a well-known newspaper.
Welcome to join the meeting!


Things about 20000 Satoshi
Let us say you had one legit $20 and one quite good photocopy of that same $20. If someone were to attempt to spend both the true bill and the fake one, someone that took the problem of looking at either of those invoices' serial numbers would see that they had been exactly the same number, and thus one of them needed to be fictitious.
This isn't a great analogy--we'll explain in more detail below. .
Once a miner has confirmed 1 MB (megabyte) worth of Bitcoin transactions, they are entitled to win the 12.5 BTC. The 1 MB limit was set by Satoshi Nakamoto, and is a matter of controversy, as some miners believe the block size should be increased to accommodate more data.
Note that I stated that verifying 1 MB worth of transactions makes a miner eligible to earn Bitcoin--not everyone who verifies transactions will get paid off.
1MB of transactions can theoretically be as small as 1 transaction (although this is not in any way common) or a few thousand. It depends on how much data the transactions take up.
In order to earn Bitcoin, you need to meet two conditions. One is a matter of work, one is a matter of luck.
2) You have to be the first miner to arrive at the perfect answer to a numeric issue. This practice is also known as a proof of work.
The fantastic news: No advanced math or computation is involved. You may have heard that miners are solving challenging mathematical problems--that is not true at all. What they're actually doing is trying to be the first miner to come up with a 64-digit hexadecimal number (a"hash") that is less than or equal to the hash.
The Facts About 20000 Satoshi Uncovered
The bad news: Because it is guesswork, you need a lot of computing power in order to get there . To mine successfully, you need to get a high"hash rate," which is measured in terms of megahashes per second (MH/s), gigahashes per second (GH/s), and terahashes per second (TH/s).
If you want to estimate how much Bitcoin you can mine along with your mining rig's hash pace, the site Cryptocompare provides a helpful calculator.
Either a GPU (graphics processing unit) miner or an application-specific look at this site integrated circuit (ASIC) miner. These can run from $500 into the tens of thousands. Some miners--especially Ethereum miners--buy individual graphics cards (GPUs) as a low-cost method to cobble together mining operations. The photo below is a makeshift, high-tech mining machine. The cards are those rectangular blocks with whirring circles. Note the sandwich twist-ties holding the graphics cards into the metal pole.
ExampleI tell three friends that I'm thinking of a number between 1 and 100, and that I write find more that number on a sheet of paper and seal it in an envelope. My friends don't need to guess the specific number, they just must be the first person to figure any number that is less than or equal to this number I'm thinking of.
9 Easy Facts About How Bitcoins Are Made Explained
Let us say I am thinking about the number 19. If Friend A guesses 21they shed because 21>19. If Friend B supposes 16 and Friend C supposes 12, then they have both theoretically arrived at workable answers, because 16<19 and 12<19. There's no"extra credit" for Friend these details B, even though B's answer was closer to the target answer of 19. .
In Bitcoin terms, simultaneous answers happen frequently, but in the end of the day there can only be one winning answer. When multiple simultaneous answers are presented which can be equivalent to or less than the target number, the Bitcoin network will determine by a simple majority--51%--which miner to honour. Normally, it is the miner that has done the most work, i.e.
The Buzz on How To Make Money Through Blogging
The number preceding has 64 digits. Easy enough to understand up to now. As you probably noticed, that number consists not only of numbers, but also letters of this alphabet. Why is that
In order to understand these letters are doing in the center of numbers, let's unpack the word"hexadecimal."
As you know, we utilize the"decimal" system, which means it is base 10. This in turn means that each and every digit has 10 chances, 0-9.


Calculate area between two data values
Working with the raster calculator | page 1 that approximates the boundary of the good elevation data 3 open the raster calculator from the spatial analyst tool bar dropdown menu less dense area are more desirable. Descriptive statistics calculator descriptive statistics calculator enter data set (up to 5000 values) answer: the sum of the fourth power of differences between data values and the mean, divided by the count minus 1 times the fourth power of the standard standard deviation [ (x1. Best answer: the area under a curve is found by integrating the equation of the curve/line the area between two curves is the integral of the upper curve minus the integral of the lower if the curves intersect and switch positions, you must reverse the order of the equations between the. The cut fill tool is used to calculate the amount of difference in each cell for a before and after raster of the same area this tool could be used to calculate the volume of earth above a given value, or between two the raster data the extract values to points tool creates a. Section 72: applications of the normal distribution to find the area between two values, we think of it in two pieces draw a sketch of the normal curve and shade the desired area calculate the corresponding z-scores. Use this simple z-score calculator solve for probability this calculator determines the area under the standard normal curve given z-score values the area represents answers, test review resources, analysis, homework solutions, help, data and information for engineers, technicians. Calculator note 9a: using a calculator to find t value of t with area 0025 above it you'll need to compare the test statistic with the critical value calculator note 9f: two-sample t- and z-intervals 2-samptint and 2-sampzint.
Math 263 section 005: class 2 : we can only calculate the proportion between two values • density curve: proportion, or probability, is area under curve the proportion of data values lying between two values is the area under the density curve between these values. Calculate areas (spatial statistics) license level: basic standard advanced summary this tool can be used to calculate an area value for a study area polygon the average nearest neighbor tool /data arcpy calculateareas_stats. The z-table calculator allows you to find the percentage of the total normal distribution that a particular data point value will be those data point values accessing the z-table calculator of 100 and a standard deviation of 20 and enter a shaded area of 910443 and select between. Unfortunately we are starting to experience performance problems with large data sets and differences in calculations due t -- calculate values select productid, cost for example if there are two columns a and b in table t and when the select query is select a, b. Descriptive statistics: standard scores and the normal distribution i) z scores a) provide information about distribution of data (area/proportions) b) steps to find area under curve i) finding an area between two scores on the same side of the mean.
Understanding t-tests: t-values and t-distributions the minitab to the null hypothesis and incorporates both the sample size and the variability in the data a t-value of 0 indicates that the sample results exactly equal the null using t-values and t-distributions to calculate. In general, there are two methods for performing overlay analysis—feature overlay (overlaying points, lines, or polygons) and raster overlay. Shading the graph the biggest find the percent of the data between -175 and 205 here there are two z-values, but each of those is a singular number and so they are represented by vertical lines on the graph the area in between those two values. Summary of video in this video we can also use z-scores to compute the percent of data that falls in an interval between two values for example • approximately 95% of the data fall within two standard deviations of the mean.
The pivot table has item in the row area, region in the column area, and units in the values area we'll see two variations on the % of to subtract one pivot table value from another it uses a special formula to calculate the index values, and is different from the. The difference between two values divided by the average of the two values shown the percentage difference between 25 and 15 is 50% here is the answer, in one line: calculate the difference (subtract one value form the other) ignore any negative sign. Related surface area calculator | volume calculator area is a quantity that describes the size or extent of a two since the longest distance between any two points of an equilateral triangle is the length of and understand that values in a circle are related through the.
Calculate area between two data values
For instance, the geometric mean of two numbers, say 2 and 8 where + is the harmonic mean of the previous values of the two sequences, then and will converge to geometric mean calculator for larger data sets. Normal distribution data can be distributed (spread out) in different ways it can be spread out 388 minutes, and the standard deviation is 114 minutes (you can copy and paste the values into the standard deviation calculator if you want) convert the values to z-scores. The probability that a standard normal random variables lies between two values is also easy to find the p(a z b) = p (z b) - p(z a the analysis involves two steps transform raw data usually stat trek's free normal distribution calculator).
- Given any data value for areas between two z-values using a ti-83/84 plus calculator, we can find a value of the area to the left of a z-score to obtain the solution using a ti-83/84 plus calculator, perform the following steps.
- P-value approach to hypothesis testing steps 1 is two-tailed, then the p-value is two times the probability the sample data produces a value equal to or these two t-values correspond to right-tail probabilies of 01 and 005, respectively since 13 is between these two t-values.
- One limitation of excel is that it doesn't have a built in function to calculate the area between two curves ellen, stephanie how to get the area between curves in excel small business - chroncom how to put two sets of data on one graph in excel.
- There are at least two ways to find that value first normdist gives the probability that a number falls at or below a given value of a normal distribution x -- the value you want to or approximately 1587% this value is represented by the shaded area in the chart above normsdist.
If we can show that our data is like the the mean we look up 1667 in a table of normal values, use the excel function =normsdist(16667) or use the online calculator what percent of the population would we expect to score between these values to find the area between two points. Can you calculate area in excel under a plotted curve by serm murmson select the data set for which you wish to calculate area under a curve 2 how to put two sets of data on one graph in excel also viewed. Standard normal distribution area under a normal curve in laboratory quality control, where it is common to make only two or three measurements the formula is used to express the number of standard deviations in the difference between a value and the mean. I'm looking for a method to calculate the area of overlap between two kernel density estimates in r how to calculate overlap between empirical probability densities (ie it always range from 0 to n, where n is set with xscale = n) # so if some of your data take negative value.


Length of base of an isosceles triangle
An isosceles triangle is a triangle in which the two sides are equal in length. Equal sides are called lateral, and the last unequal side is called the base of the triangle. By definition, every regular triangle is also isosceles. An isosceles triangle has the following properties:.
- base angles are equal
- the base bisector is the median and height
- the median to the base is the bisector and the height
- the height drawn to the base is the bisector and the median
Find the base of an isosceles triangle зная сторону и высоту


GeoGebra is a software application for mathematical computing at all levels. This program collects geometry, algebra, spreadsheets, charts, diagrams, statistics, and differential calculus in a simple and compact package. This software is one of the leading products in the field of dynamic computing in various mathematical branches. The uses of this product can be very general and can be used to perform mathematical calculations for students every day.
More To Read
The GeoGebra user interface is very simple and user-friendly. Of course, this is not simply a deficiency in the ability of this program. Another great feature of the program is the ability to create educational web pages. Based on calculations and graphics charts, you can design web pages for textbooks and share them with others. This app is free of charge and for non-commercial purposes, there is no limit to its use.
Download File:direct link


This meeting will address formulation issues, numerical methods, and the implementation of algorithms for probing molecular models, especially multiscale simulation methods. We will bring together mathematicians and computer scientists with physical scientists, to accelerate the transfer of theoretical methodology mathematical ideas into applications.
Note: it is anticipated that the meeting will be wider than these topics, but many of the invited presentations will be focussed on these issues.
Multiscale formulation of molecular problems, e.g. path sampling algorithms
Adaptive and parallel algorithms
Methods for finding reaction pathways, free energies and rates
Sampling methods based on dynamics and stochastic dynamics
Applications to biomolecules


United Nations - UNECE
Please be careful when you run the code. Truncated Poisson Distribution Notice, however, when Y = 0 the denominator vanishes, hence R is undefinable. To render this problem, one must truncate the range of Y in such a way that P(Y = 0) = 0, the probability that Y takes on the value zero is zero; and consequently P(Y > 1) = 1, or the probability Y takes a value larger than zero is one. I have a zero-truncated distribution, and I want to test if it's Poisson distributed.
Let X1,, X, Be A Random Sample Of Size N From This Truncated Poisson Distribution (i) Show That The Sample Mean X Is A Biased Zero-inflated data indicates that the data set contains an excessive number of zeros. The word zero-inflation is used to emphasize that the probability mass at the point zero exceeds than the one allowed under a standard parametric family of discrete distributions. Gupta et al.,1 Murat & Szynal,2 Patil & Shirke3 have contributed to estimation and testing of the parameters involved in Zero 2019-01-06 The zero-truncated multiplicative-binomial distribution is derived and investigated. In particular, the maximum likelihood estimators of the parameters and their asymptotic variance-covariance matrix are obtained. The simulation procedures for generating data from zero-truncated multiplicative binomial distribution using R-software and are given. Here we derive the formulas for the mean and variance of a zero truncated binomial distribution.
What is truncation? Truncated distributions arise when some parts of a distribution are impossible to observe. 2020-08-18 · A truncated probability distribution is one derived from limiting the domain of an existing distribution.
LS-DYNA R10.0.0 R10.118302 released — Welcome to the
We all know that in math, it is not possible to divide a number by zero. SQL Server Transaction Log Backup, Truncate and A normal distribution curve is unimodal ( it has only one mode). The curve is symmetric about the mean.
Models and Methods for Random Fields in Spatial Statistics
Under these assump- Second, for a suitable truncation ˆXn of. Xn such that ˆXn treatment of the bivariate normal distribution--presenting entirely new material on Handbook of the Normal Distribution, Second Edition 0 Recensioner. evaluation for a coal-fired power plant of near-zero air pollutant emission The improved distribution method of negentropy and performance evaluation of Anisotropic model with truncated linear dispersion for lattice and interfacial tistical Decision Proceduros and Zero-Sum Two-Person Gamua . CONEN, Jr.: Estimation of Paramotorn in Truncated Penrhon Frequency Distributions 250. 306, 304, Bernoulli distribution ; binomial distribution ; point binomial, binomialfördelning. 307, 305, Bernoulli 940, 938, difference of zero, #.
Se hela listan på stats.idre.ucla.edu
2011-09-12 · truncated distributions can be used.
Fullmakt vid dödsfall
evaluation for a coal-fired power plant of near-zero air pollutant emission The improved distribution method of negentropy and performance evaluation of Anisotropic model with truncated linear dispersion for lattice and interfacial tistical Decision Proceduros and Zero-Sum Two-Person Gamua . CONEN, Jr.: Estimation of Paramotorn in Truncated Penrhon Frequency Distributions 250. 306, 304, Bernoulli distribution ; binomial distribution ; point binomial, binomialfördelning. 307, 305, Bernoulli 940, 938, difference of zero, #.
Gaussian is defined to have zero skewness and zero excess kurtosis, when the skewness and kurtosis are far from zero, it implies that a Gaussian
Aug 14, 2018 The so called zero truncated Poisson (ZTP) distribution is a discrete probability model whose support is the set of only the positive integers ()+I. Here, we first propose three-parameter model and call it as the compound zero- truncated Poisson normal (ZTP-N) distribution. The model is based on the
Density function, distribution function, quantile function and random generation for the Zero-Truncated Binomial distribution with parameters size and prob.
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Viewed 528 times 3 $\begingroup$ Closed.
PDF Comparison of the Chapman–Robson and regression
However, one of my variables is truncated at zero, but has most of its density around zero. This distribution is sometimes called the extended truncated negative binomial distribu-tion because the parameter r can extend below 0. B.3.2 The zero-modified subclass A zero-modified distribution is created by starting with a truncated distribution and then placing an arbitrary amount of probability at zero. This probability, PQ1, is a Se hela listan på stats.idre.ucla.edu Setting p0 = 0 deﬁnes a subclass of so-called zero-truncated distributions. The members of this subclass are the zero-truncated Poisson, the zero-truncated binomial, the zero-truncated negative binomial and the zero-truncated geomet-ric.
B.3.1 The zero-truncated subclass. The members of this class “Use of the Left-Truncated Normal Distribution for Improving Achieved Service \ sigma>0.


Recently I decided to see how Google Drawings could help with another math topic: telling time. This is a Common Core Math standard for grades 1, 2, and 3:
- CCSS.MATH.CONTENT.1.MD.B.3 - Tell and write time in hours and half-hours using analog and digital clocks.
- CCSS.MATH.CONTENT.2.MD.C.7 - Tell and write time from analog and digital clocks to the nearest five minutes, using a.m. and p.m.
- CCSS.MATH.CONTENT.3.MD.A.1 - Tell and write time to the nearest minute and measure time intervals in minutes. Solve word problems involving addition and subtraction of time intervals in minutes, e.g., by representing the problem on a number line diagram.
To address this I created a Google Drawing template with an analog clock face and two rotatable clock hands. See below for a link to get your own copy of the interactive clock template, as well as directions for using it.


I began my teaching journey with Teach for Australia, a not-for-profit organisation with the mission to address educational disadvantage in our country. Through this program, I obtained a Masters of Teaching, specialising in Internationalisation and with Maths, Science and Environmental Science as my learning areas. My teaching placement through Teach for Australia took me to Numurkah Secondary College, where I gained 2 years of experience teaching maths at years 7, 8, 9 and 10, to students who displayed a wide variety of learning needs and abilities. I was then lucky to gain 3 years of experience teaching at St Michael’s Grammar School in Melbourne. Here I taught year 7 through to year 10 as well as VCE Mathematical Methods and VCE General Maths at the year 11 level. After leaving teaching to have kids, and missing the interaction with students and the satisfaction of helping them, I decided to start doing private tutoring. I am especially interested in the home education scene, and hope to be able to support families who are transitioning out of the school system as a result of the challenges presented in the Covid era. I love teaching and I hope to continue to build confidence in maths within the students under my care. I am registered with the Victorian Institute of Teaching, and I have a Working With Children Check and a Police Background Check.
0411 364 131


The Pythagorean Theorem Worksheet
Special Right Triangles Worksheet
Linear quadratic systems
Why the flowers have 3 or 5 petals? Why we do not have circular or square mobile screens? Why the galaxies are spiral? 1. ...
How to Check if Pair of Straight Lines Intersect
Ancient Indian Mathematicians (like Bhaskaracharya) knew and practiced the concept Infinity, How? we explore in this article. Click to read more.
Equation of Pair of Straight Lines Perpendicular to Two Given Lines
Visit the post for more.
How to Find Image of a Point About the Line
Converting between percents decimals and fractions


Number of Months between two dates Page 2 - Microsoft
Sometimes you need to be able to determine the amount of time between dates in years and months. For example, you can determine that the amount of time elapsed between November 23, 1960, and May 13, 2014, is 53 years and five months.... 2/10/2016 · How to get number of months and years between given dates Here are my three ways to calculate the number of months and years between two given dates in Java.
How to calculate Months Between two dates
There are 6 months between the two dates if the dates are considered to have the same year. The year it taken from Date1, not Date2. This makes a difference when one year is a leap year. Since 2007 is not a leap year, 29-Feb is not counted. See DATEDIF And Leap Years below.... I want to calculate difference between two dates and difference of months if greater than 6 months is to be rounded off to next one year and output to be give in years.
How to calculate elapsed time/days/months/years between
Say you’d like to calculate the difference between two dates in terms of number of months. The following simple function will do just that: return the absolute number of months between two dates: how to find someone who sells weed 5/09/2012 · Re: How to Calculate Exact No. of Months between Two Dates This is all subjective, there is no right or wrong answer for what "Exactly 1 month" is. Because of course not all months …
Calculating years months and days between two dates
-- Get the number of months between February 29, 2012 and February 01, 2012 SELECT MONTHS_BETWEEN (DATE '2012-02-29', DATE '2012-02-01') FROM dual; -- Result: 0.903225806 Note that MONTHS_BETWEEN always calculates the fractional part as the difference in days divided by 31. how to get a flat stomach in two weeks MONTHS_BETWEEN returns number of months between dates date1 and date2. If date1 is later than date2 , then the result is positive. If date1 is earlier than date2 , then the result is negative.
How long can it take?
Calculate Number of Years Months and Days between 2 dates
- How to calculate exact number of months between two dates
- How to calculate Months Between two dates
- how to get date difference in years month and date
- Number of Months between two dates Microsoft Power BI
How To Get Years Months Between Two Dates
13/03/2014 · This tutorial shows you how to calculate the number of years, months and days between two dates using the undocumented DATEDIF function in Excel Category Howto & Style
- "YM" calculates the number of months between two dates as if the dates are in the same year (row 6). "MD" calculates the number of days between two dates as if the dates are in the same month and year …
- SQL to display all months between two dates. Oracle Database Tips by Donald BurlesonNovember 23, 2015
- 16/08/2017 · Re: counting months between dates and returning a decimal Thanks for the previous contributors, much appreciated. You have allowed me to determine solutions for determination of months as a fraction between two dates.
- -- Get the number of months between February 29, 2012 and February 01, 2012 SELECT MONTHS_BETWEEN (DATE '2012-02-29', DATE '2012-02-01') FROM dual; -- Result: 0.903225806 Note that MONTHS_BETWEEN always calculates the fractional part as the difference in days divided by 31.


Dynamic stochastic general equilibrium models with ex-post heterogeneity due to idiosyncratic risk pose numerous challenges stemming from the cross-sectional distribution of endogenous variables which changes stochastically over time due to aggregate risk. In this thesis, I tackle various open questions. My first contribution is of a theoretical nature as I establish existence and uniqueness of the Aiyagari-Bewley growth model. The second challenge I address has a more practical concern. I propose a new numerical method to compute solutions to heterogeneous agent models. With the derived approximation error bounds, I ensure convergence to the rational expectations equilibrium. Equipped with this novel theoretically founded method, I show that even two standard economic models like the Aiyagari-Bewley growth model and the Huggett economy yield intriguing results. When agents progressively share idiosyncratic risk, heterogeneity increasingly amplifies aggregate risk. Furthermore, the volatility of the expected stationary cross-sectional distribution and of the stationary price distribution rises.


The establishment of the Faculty of Science was by a Ministerial Decree No. 80 of 2014 in April 2014. It includes departments of Applied Mathematics and Statistics, and Computer and Information Technology.
The Faculty of Science awards a Bachelor’s degree (Honors) in each of the following specializations in 4 years.
- Each program has a minimum of 165 credit hours
- The Faculty adopts the amended semester system. Each program is completed in 8 semesters for a period of 15 weeks, excluding exams
The Faculty’s specializations are Systems and Technology – Applied Mathematics – Statistics.


What is the effective resistance, calculated value of reactance, the Q, and bandwidth? ... C and L in parallel Calculator', please fill in questionnaire.
Working of Resistors in Parallel Calculator. This parallel resistance calculator calculates the total resistance value for all the resistors connected in parallel. Just add the number of resistors in the first column, and then enter the values of each resistor with selecting the proper unit in Ω, KΩ or MΩ. This calculator determines the resistance of up to 10 resistors in parallel. Enter resistances into the boxes below and when all values have been input, click on the 'calculate' button and the result will appear in the box below that button.


Visually Do Shape Analysis !
by Prof. Yukari Shirota (Gakushuin Univ., Japan),
Prof. Riri Fitri Sari (Univ. of Indonesia),
Dr.Tetri Widiyani (Sebelas Maret University, Indonesia), and
Prof. Takako Hashimoto (Chiba University of Commerce, Japan),
Abstract: Recently a new morphometric statistical analysis has been growing.
This analysis was developed by the University of Leeds in 1998 called statistical shape analysis or commonly known
as geometric statistics. Using this statistical analysis we can measure the change in the shape of an object or
so-called deformation, easily. The problem on transforming data sets in the different size, orientation and shape
of an object into a coordinate system had been very difficult, over years.
By this analysis, we can be quantified the shape of an object by eliminating information of location,
rotation, and scale. However, the mathematics is a bit difficult to understand.
To solve the problem, this teaching material web site.
Here we will explain the math process visually. Visualization has the power to make people
understand the content meaning at a glance. The visualization power is required in mathematics education.
We have developed and used many visual teaching materials for our university math lectures.
The teaching materials of the shape analysis have developed
as a joint research project result of Japan and Indonesia researchers.
They are Prof. Yukari Shirota (Gakushuin Univ., Japan), Prof. Takako Hashimoto (Chiba University of Commerce, Japan),
Prof. Riri Fitri Sari (Univ. of Indonesia), and Dr.Tetri Widiyani (Sebelas Maret University, Indonesia).
The project was supported by the Computer Centre of Gakushuin Univ. as a 2017 special rsearch project.
Using the teaching materials, we will do the tutorial lectures in
IEEE DSAA (Data Science and Advanced Analysis) 2017
to be held on 19-21, Oct. 2017 in Tokyo.
We would like to explain the mathematics visually and interactively.
We hope that the readers access the visual materials for themselves.
The graphics were written in Wolfram CDF. With the free software $B!H(BWolfram CDF player$B!I(B
everyone can operate the graphics.
In addition, we eagerly hope that more people who need mathematics enjoy the mathematics
using the visual materials.
1. Dryden, I.L. and K.V. Mardia, Statistical shape analysis with Applications in R (Second Edition). 2016: J. Wiley Chichester.
2. Mardia, K., F. Bookstein, and J. Kent, Alcohol, babies and the death penalty: Saving lives by analysing the shape of the brain. Significance, 2013. 10(3): p. 12-16.
(1) Deformation between Homo floresiensis and Homo sapience
Figure 1: Homo floresiensis (left, blue) and Homo sapiens (right, yellow)
photos with the 18 landmarks and the two configurations (centre).
First, let us show the interesting analysis results to the audience
so that the audience can understand the goal of the shape analysis.
Let's see the craniofacial differences of the two ancient humans;
they are Homo floresiensis (left) and Homo sapiens (right)
(See Figure 1).
We would like to thank the Director Sukronedi (S.Si, M.A.) and staff members of Sangiran Early Man Site Museum,
Indonesia for giving us a permission of an access to the ancient human craniofacial collections.
In Indonesia, we can discover various bone fossils of early men, including craniofacial bones,
especially in the vicinity of Solo city, Indonesia.
Concerning Homo floresiensis, controversial discussion has occurred,
when Homo floresiensis was found in an isolated island named "Flores" in Indonesia.
In the materials, let us see the local changes between the two early men's photos
using the statistical shae analysis.
We set the 18 landmarks are given on a skull photo.
The same number means that they are corresponding positions.
We would like to analyse the local movements/changes between the corresponding landmarks.
For example, the forehead became wider or the chin was getting smaller.
Using the shape analysis, we can divide the deformation to the Affine transformation and
The Affine transformation can express how the total plane change is such as skewing. However,
the Affine transformation cannot express the local movements.
The local movements can be expressed as a non-Affine transtformation.
Figure 2: The deformation of the two pre-shapes.
First, the given condiguration must be moved to the centre (centering) and then divided by the centroid size
(scaling). The resulting shape is called a pre-shape.
Figure 3: The deformation is divided to Affine and non-Affine transformations.
The deformation in Figure 2 is divided to the Affine and the non-Affine transformations.
Figure 4a: A pair of thin-plate splines for the deformation.
The deformation can be mathematically expressed by a pair of thin-plate splines.
The deformation include both the Affine and non-Affine transformations.
Let's open the graphics which needs in advance to install the Wolfram CDF player.
In the graphics, there are two sliders by which you can move the #1 landmark position
x and y. When you change the x value of the #1 landmark, only the first spline will be changes.
Let us change the x value to be positive and negative; then the point of the first spline surface will
go up and down. We think that this interactive operation on the graphics would make you surely understand
Figure 4b: Spline base functions make the thin-plate splines.
Let us explain how to make the spline surface.
The interpolation can be made by Spline base functions.
The function has the just one local maximum point. We set the point
at each landmark position. Then we find the minimum point so that
the total landmark points would be connected most smoothly.
The resultant interpolation is displayed in the graphics. At the
time, the bending energy of the pair of thin-plate Splines is minimum.
Figure 5a: The top 6 principal warps of the Homo floresiensis' (left) preshape.
Given a photo with landmarks, we can obtain the foundamental characteristics
of the landmark layout. First we make a bending energy matrix of the given
shape and calculate the eigenvectors of the matrix.
Later, we shall explain the bending energy matirx.
The individual eigenvector times (inner product) the above-mentioned Spline base functions becomes
the surface shown in Figure 5a. The surface is called a principal warp.
The eigenvalue is called the bending energy.
In Figure 5a, the principal warps of the Homo floresiensis' (left) preshape
are illustrated. The number of principal warps is 18 -3 = 15 in this case.
Because there is not enough space on the web page, only top 6 partial warps are displyed,
although the number of principal warps is 18 -3 = 15 in this case.
If you learn PCA (Principal Component Analysis), an analogy would be helpful.
Given the configuration of the landmarks, the principal components of the configuration
are extracted like this.
Figure 5b: The top 5 principal warps of the Homo floresiensis' (left) pre-shape.
Let's move the principal warps by moving the #1 landmark which is red marked.
Please remember that the landmark movement changes the partial warps; although
you need not analyse the changing rules (The authors do not identify the changing rules, too.)
Figure 5c: The principal warp eigenvalues of the Homo floresiensis' (left) pre-shape.
Next let's see the principal warp eigenvaues which are shown in the bar chart.
There are 15 eigenvalues. The biggest one is about 600 and the second one is about 400.
Figure 6: The top 3 partial warps of the non-Affine deformation from Homo floresiensis' to Homo sapiens.
The non-Affine transforamtion of the deformation can be expressed by the
The partial warp is a mapping of the thin-plate spline transformations to the principal warp.
Figue 6 shows the partial warps of the non-Affine formation from Homo floresiensis' to Homo sapiens.
From left to right, the first partial warp to the third partial warp are illustrated.
In each figure, both the original shape and the partial warp are shown.
The differencial vector of each landmark lines up on a straight line (See the
centre of each figure around the origin).
In the shape analysis, the partial wapr is important. The partial warp can give us
which landmarks changes much or less and the change directions.
In figure 6, no big change can be seen in the second partial warp.
(2) Deformation between a relaxed cat and an angree cat
Figure 7: When a relaxed cat gets cross and arches its back, the 9 landmarks get nearer to the centre.
In the section, using a simple deformation, the math process will
be explained visually. In the section, a shape, not a pre-shape, is
Figure 8: The deformation of the flatten can got cross. (non pre-shapes)
As shown in Figure 8, we plot the 12 landmarks on the cat back.
In Figure 6, the deformation, its Affine transformation and its
non-Affine transformation are shown.
In the Affine transformation, we can see the shrink of the
In the non-Affine tansformation, we cann see the local movement
of the 6 landmarks at the centre.
Figure 9: Thin-plate spline interpolation of the cat deformation.
The deformation can be expressed by a pair of thin-plate splines.
Figure 10: Bending energy matrix of the relaxed cat.
Let's calculate the bending energy matrix of the relaxed cat.
Figure 10 shows two matrices. First, we make the first matrix.
The matrix S of which size is 12 times 12 is calculated by the spline base function.
The matrix T is the given shape T; in the case, the shape of the relaxed cat.
Then we calcurate the inverse matrix of this matrix.
Next, take the right-upper part of which size is 9 times 9. This is the bending
energy matrix (See the matrix at the bottom).
Figure 11: The relaxed cat$B!G(Bs 9 principal warp eigenvalues and 2 eigenvectors.
Next let us calculate the eigenvalues and eigenvectors of the bending energy matrix.
In the left figure, the bar char of the eigenvalues are shown. There we can see
the biggest eigenvalue is about 10 and the second one is nearly 6.
In the center of the figure, two eigenvectors are shown. The upper one
shows the first eigenvector which consists of 12 factors.
Each factor shows each landmark's contribution to the first partial warp;
the red marked landmark's factor value is negative about -0.06 so the point
becomes a valley in the spline surface. Concerning the second landmark,
the factor value is about 0.3 so the point becomes a mountain.
Figure 12: The relaxed cat's first principal warp.
Let's see the function of the first principal warp (See Figure 12).
That is a inner product of the eigenvector and the spline base functions
at each landmark positions.
Figure 13: The 6th partial warps of the deformation
Finally, the partial warps of the deformation are shown.
Although we can obtained the 9 partial warps, the first to the
fifth partial warps did not show a large local movements, just a
subtle change. In the sisth partial warp, we fist identified the
local movement as shown in Figure 13. They are horizontal directional
movements. As shown in the above, the scaling changes
are involved in the Affine transformation.
We shall conclude the materials here. We explained the parial warps of
the shape analysis. In addition, explanations of the analysis of variance (ANOVA) would be needed.
However, the ANOVA is lectured in statistics lectures. So we skip the ANOVA.
The most surprising point of the shape analysis is discovery of the
principal warps from the bending energy matrix, the authors think.
Every time we use the shape analysis method, we wonder how was it inspired
so that they would have the idea of the bending energy matrix.
We are interested in an economics data analysis, too. So we are conducting
some researches on the economics data such as stock prices.
We hope that much more researchers in various fields leverage the new analyis
(1) Yukari Shirota, DSc.
Prof. of Faculty of Economics, Gakushuin University, 1-7-1 Mejiro, Toshima-ku, Tokyo, Japan
Research fields are visualization of data on the web, social media analysis, and visual education methods for business mathematics.
1. Yukari Shirota: "Selected graphics and papers",
2. Yukari Shirota: "Mathematics Graphics Materials",
(2) Dr. Ir. Riri Fitri Sari MM MSc
Prof. of Department of Electrical Engineering, Faculty of Engineering, University of Indonesia, Kampus Baru UI, Depok 16424, Indonesia, email@example.com.
Her current main teaching and research area includes Computer Network, Protocol Engineering, Network Computing, Sustainability in Higher Education, Applications of ICT for Humanities.
(3) Dr. Tetri Widiyani
Tetri Widiyani is a Senior Lecturer at the Department of Biology of the Sebelas Maret University (UNS), Solo, Indonesia. She was awarded with a PhD from Biology from Bogor Agricultural University, IPB, Bogor, Indonesia. She is an editor of some Journals in Biology in Indonesia.
(4) Takako Hashimoto, Ph. D.
Prof. of Faculty of Commerce and Economics, Chiba University of Commerce 1-3-1, Konodai Ichikawa City, Chiba, Japan
Chair, IEEE Women In Engineering (2015)
Coordinator, IEEE R10 Women In Engineering (2011-2014)
Past Chair, IEEE Japan Council Women In Engineering (2012-2013)
Visiting Researcher, UCLA (2015)


With grants from the Hewlett-Packard Catalyst Initiative and the National Science Foundation, Northwestern University has acquired HP tablet laptop computers and Fourier sensors that will be available for temporary loan to Chicago area schools. The goal of this project is to increase the use of technology in math and science classrooms and to facilitate access to online laboratories, such as the iLabs network (www.ilabcentral.org).
This summer, teachers from the Chicago area participated in a workshop to learn how to use the HP tablets and Fourier probeware. They wrote hands-on classroom activities for their middle and high school courses which you can view here.
See students and teachers from Chicago area schools using the HP tablets to do online iLabs and other OSEP-developed curricula.
Interested in using our HP tablets and Fourier sensor kits? Apply here.


Seung Eun "Rina" Park conducts quantitative research on the impact of financial aid program to college enrollment and labor market outcomes.
Park is a doctoral student in the economics and education program at Teachers College, Columbia University. She holds an MA in statistics from Stanford University and a BA with double majors in applied mathematics and economics from the University of California, Berkeley.
Prior to joining CCRC, Park worked as a research assistant for the Center for Education Policy Analysis (CEPA) at Stanford University. Her research interests include higher education finance, fiscal federalism, and correctional education.


Algebra is a tricky subject. Many a times, even a lot of practice can’t save you from making some silly mistakes.
But how do even strong students end up falling in these common traps? One of the reason is being too quick to answer the question without getting into details. Students, generally hurry while solving Algebra problems and this opens the door to multiple silly mistakes which in turn affect their overall score.
In order to stay away from these mistakes, it’s important to focus on the basics and double check the problem and answer. If a student is successful in avoiding these silly mistakes, nothing can stop him/her to stay ahead in the learning curve.
While there are many silly mistakes one can encounter while solving Algebra, here are the most common ones mentioned by Etutorworld:
Adding Different Terms Together:
This is perhaps the most common problem in algebra. While solving problems, students tend to miss out on the fact that letters and numbers are two different entities. When students come across equations like “5a + 10” they add them both without considering much. The resulting answer for them is 15a.
But that is absolutely wrong. Both of these are different terms and cannot be added. 5a cannot be added with just 10!
This process works out if the equation consists similar terms such as 67a+9a. These are similar terms as both have the letter “a” in it.
But when it comes to the 5a + 10 equation, it cannot be simplified any further and thus must be left as it is.
The best way to solve an algebraic equation is by arranging all the similar terms together followed by the numbers mentioned in a question and then do the calculation.
5a + 10 + 12 + 7a
5a + 7a + 10 + 12
12a + 22 would be the final answer here.
Missing Out Brackets:
The next most common mistake while doing Algebra is the failure to solve the brackets in the right order. This changes the entire equation and the possible answer. Let’s consider an example:
“a + 2 x 3” vs “(a + 2) x 3”.
Both of the equations look same, right? Although it’s not. Both of them will be solved differently and answers would be different as well.
According to the rule of BODMAS multiplication comes before sum operations. So, for the first equation, one has to multiply the numbers first.
However, for the second equation one has to solve the bracket area first since that comes before all operations as per BODMAS. Thus while reading the question, it’s crucial to be aware of the brackets and how they are arranged.
Missing out Fractions:
For example, if the first number is b and the second number is 3, find out the mean of the two?” In order to solve this problem, many students would write b+3/2, agreed?
Unfortunately, this is wrong.
In reality, the final answer must be (b + 3)/2. In order to find out mean, you need to add the numbers first and then division process takes place.
While some may be an expert in Algebra, others may not be so strong. For such students, a little additional help is required. For this purpose, algebra tutoring can be considered. Many a time, one-to-one teaching works wonders as it addresses the student’s problem at the grassroot level. If the concepts are made clear, the rest is achievable.
Algebra is a fun subject provided you are doing it properly. It’s true that it requires a lot of patience and caution to details but once your basics are solid, you are good to go.
Think of it as a mystery you are trying to solve. Keep your alert sharp and focus straight. The rest will fall in place.


For Geeks & Brainiacs #06- Trading Places -
An ant is on one side of a branch and a fly is on the other side of the branch.
For a change of scenery, they decide to swap places. So the ant crawls along the branch from A to B and
the fly crawls along the branch from B to A. They each travel in a perfectly horizontal line. After they
pass each other, it takes the ant 20 seconds to reach point B, while it takes the fly only 5 seconds
to reach point A. How much time did it take each insect to make the journey?
Do you have a suggestion
for this puzzle (e.g. something that should
be mentioned/clarified in the question or solution, bug, typo, etc.)?


Nicole Hoover, Assistant Teaching Professor
Nicole Hoover received her B.S. in Mathematics from San Jose State University and later earned her M.A. in Mathematics from the University of California Davis. She served in several instructional capacities at UC Davis, Cosumnes River College, and the University of New Orleans before joining UW Bothell in 2006. She became the director of the Quantitative Skills Center from 2006 to 2009. Returning to UW Bothell in 2012 as a part-time instructor, she was appointed as a full-time instructor in 2015; in those roles, she has taught a wide variety of courses ranging from pre-calculus to junior level matrix algebra.
University of California, Davis
- M.A. Mathematics
San Jose State University
San Jose, CA
- B.S. Mathematics


Applying these rules to solve genetics problems involving many genes. calculate the frequency of the recessive class not for an Aa x Aa cross, not for an AaBb. See how to calculate probabilities in genetics for a dihybrid cross. 5. • Probability calculations are used in genetic problems to predict the outcome of crosses. • To compute probability, we can use three mathematical operations.
Two basic rules of probability are useful in solving genetics In a Mendelian cross between pea plants that are heterozygous for flower color. For his work, Mendel is often referred to as the “father of modern genetics. ” Mendel . Calculate the probability of traits of pea plants using Mendelian crosses. Penguin Prof Helpful Hints: How to Solve Genetics Problems . For example, in the cross AaBbCc with AaBbCc, find the probability of an offspring that is aabbcc .
From the last lecture, we followed gene segregation in a cross of a true breeding . Many problems in diploid genetics rely on basic concepts of probability.


Mathematical fashion focuses on mathematics and the science of numbers. It usually uses designs that are based on mathematical patterns, shapes, and equations.
The mathematical fashion industry is booming, with all types of products available for sale online. From t-shirts to socks, there are so many different items you can buy in order to show your love for math!
Math is everywhere, and it is not just in the classroom. It is in the movies, on TV, and even on your shirt.
Wear Math Shirts!
Math has been a trending topic for quite some time now. People are showing their love for math in different ways – from wearing math-related clothing to buying books about math.
It wouldn’t be wrong to say that people are obsessed with numbers and mathematical concepts these days.
There are many different types of fashion. Some are more practical, and some are just for fun. Mathematics is a type of fashion that is both practical and fun. People can wear mathematical t-shirts to show their love for math!
Math is a subject that people are often afraid of. But math can be fun and trendy too! There are many cool mathematical fashion trends that you should try out.
There are three different types of mathematical fashion-
- Math in the form of shirts, dresses, and other clothing items with mathematical patterns or designs on them.
- Mathematical patterns in tattoos and body art like henna tattoos and temporary tattoos.
- Mathematical patterns in hairstyles like braids, cornrows, dreadlocks, etc
Math is not just for the classroom anymore. People are wearing shirts with math on them, and it’s not just for kids.
How Math Fashion Started
Math fashion is a new trend that started in the late 2000s, and it has been catching on ever since. There are three types of mathematical fashion: geometric, algebraic, and trigonometric. Geometric style can be found in art, clothes, and other designs that use geometric shapes like circles or triangles. Algebraic style is more about using math to create patterns, like using a pattern of dots to make a t-shirt design or using different colors to make a shirt design pop. And trigonometric styles use numbers like 3, 4, 5, etc., which are often used in patterns of lines or dots to form designs like t-shirts with fractions on them.
There are many reasons why you should wear a math shirt. One of the main reasons is because it will make you laugh and smile every day. It will also make you feel more confident in your abilities and make others around you laugh as well.
Wearing a math shirt on your day off might not seem like the best idea at first, but it will turn out to be one of the best decisions you’ve made in your life.
You can use math to help you in your everyday life. You can also wear a Math shirt to make you smarter by making you more confident in your skillset and less likely to get nervous when solving math problems.
Math is everywhere, so it’s important for people to be able to communicate with those who understand it better than they do.


Get ideas from other Pi Day fans on what they’d do – at school or home – to celebrate Pi Day.
Get crafty with an embroidery project on Pi Day.
The law sometimes doesn’t get its math right.
Spoiler alert: 3.14 backwards spells Pie.
Download our press kit or get widgets for your blog to spread the news about Pi Day.
An Android app that helps you learn the digits of Pi.
Princeton has an annual party celebrating Pi Day and Einstein’s birthday (also March 14).
Activities for Pi Day: eat pie, eat pie, make something cool, eat more pie, sing a song, eat more pie.
A huge spiral of dominos whose colors make the Pi symbol. Construction appears to have taken over an hour, but the time-lapse makes this video a clever 3 minutes 14 seconds.
They must sell a lot of pies on Pi Day.


"If you are able to solve the problems in Maths, then you are able to solve the problems in your life."
Mathematics laboratory is a place where anybody can experiment and explore patterns and ideas. It is a place where one can find a collection of games puzzles and other teaching and learning material. The material is meant to be used both by the students on their own and with their teacher to explore the world of mathematics, to discover, to learn and to develop interest in mathematics. The activities create interest among students who want to explore, and test some of their ideas and beliefs about mathematics.
Samsara's mathematics Lab was inaugurated successfully on Feb 8th , 2017 by our Managing Director, Mr. Vikramjeet Singh Shastri and our Principal Capt. Praveen Roy. They cut the ribbon and opened the Math lab to the school students. Some of our great Indian Mathematicians like Aryabhatta, Ramanujan and Shakuntla Devi. Then we showcased our lab with our variety of Lab kits which were meant for juniors and seniors.
In junior section, we have abacus, skip counting, Ascending and Descending ladder, Integer tiles, 2-D and 3-D shapes, fraction Tower various informative charts and many more. In senior section, we have Ganitmala, magnetic disks, Cuisenaire strips, ring of theorems, Algebraic identities kits, geoboard, Pythagoras theorem, Models of Solid shapes etc.
Our Lab is a place to enjoy mathematics through informal exploration. It is a place where the child can generate problems and challenge themselves to get an answer. It is a place to explore and design new mathematics activities. So our lab is not to be used to assess students' knowledge of mathematics. We assess students' knowledge beyond the curriculum.
So our lab is a self explanatory lab wit activities in which students can come anytime(when they are free) and engage in the work, continue working on the problem and take teachers help as and when they feel the need.


This percentage calculator tool is a free online calculator to quickly and easily calculate percentages.
What is the percentage increase/decrease
Use the tab key to move to the next field and shift + tab to move to the previous field.
A percentage is a number that represents a fraction of the whole amount being 100. You will often see a percentage written with the symbol "%" or simply as "percent". It can also be denoted as "pct."
Percent is another name for indicating hundredths. So 1% is one-hundredth, that means in decimal form, 1% is 1 / 100 = 0.01. If you were to have 25%, it is equivalent to the decimal 0.25, or the fraction ¼ or 25/100.
The percentage formula is simply just an algebraic equation involving three values.
The percentage calculator provided above automatically converts the input percentage into a decimal to compute the solution.
Percentage Difference Formula
If you want to find the difference between two values, then you use the percentage difference formula to work this out.
The percentage difference between two values is calculated by dividing the absolute value of the difference between two numbers by the average of those two numbers.
Multiplying the result by 100 will yield the solution in percent, rather than decimal form.
Percentage Change Formula
If you are trying to work out what is the percentage increase and decrease, then it is calculated by computing the difference between two values and comparing that difference to the initial value.
This involves using the value of the difference between the two values, and dividing the result by the initial value.
Ready to take your
financial management to the next level?


Given two integers M and N the duty is to assemble a binary palindromic string consisting of M occurrences of 0s and N occurrences of 1s.
Enter: M = 4, N = 3
Clarification: The string 0011100 is palindrome containing
4 occurrences of ‘0’ and three occurrences of ‘1’.
Enter: M = 3, N = 3
For the string to be a palindrome, atleast one amongst M and N needs to be even, in any other case if each M and N are odd then string cannot be a palindrome.
Observe the under steps to unravel the issue:
- If each M and N are odd then print -1.
- If N is Even, print ‘1’ N/2 occasions, then print ‘0’ M occasions, then once more print ‘1’ N/2 occasions.
- If M is Even, print ‘0’ M/2 occasions, then print ‘1’ N occasions, then once more print ‘0’ M/2 occasions.
Under is the implementation of the above strategy:
Time Complexity: O(M+N)
Auxiliary Area: O(1)


i need fixt it For question 2a, check the “id” variable to be sure you have the correct cases numbers that need to be removed. There are three cases that should be removed that you did not list. Also, 18 and 1129 will automatically be removed since there is missing data for these cases (no MAH_1 value). Some of your values are different than what I have. Be sure you run the multiple regression with the profile-b data set and only with cases that are MAH_1 ≤ 22.458. For question 2h, you should not include the values for the variables that are not statistically significant. The regression equation should only include those variables that are statistically significant. For 2i, also mention that these two variables are not statistically significant and provide the p (sig) value.
Unformatted Attachment Preview
1. The following output was generated from conducting a forward multiple
regression to identify which IVs (urban, birthrat, lnphone, and lnradio) predict
lngdp. The data analyzed were from the SPSS country-a.sav data file.
a. Evaluate the tolerance statistics. Is multicollinearity a problem?
In order to evaluate the presence of multicollinearity, we can exploit the tolerance
statistics, calculated as 1-R2. A small tolerance is an indication of the fact that the
variable considered is almost a perfect linear combination of the other independent
variables already in the equation. Usually, a value of 0.1 serves as the cutoff point.
Looking at the table, we can see assess that multicollinearity is not a problem because all
tolerance statistics are greater than .1 for all the independent variable in both
b. What variables create the model to predict lngdp? What statistics support your
The model summary output indicates that the variables used for the forward multiple
regression are are respectively lnphone (for the simple regression) and lnphone +
birthrate (for the multiple regression).
If we look at the p-values, we can see that both of the coefficients are statistically
significant in explaining the variation of lngdp. However, that of birthrat is significant at
a 5% significance level, differently from that of lnphone which is significant at 1%
significance level. Moreover, despite its significance, the coefficient of birthrat is rather
small in magnitude and the R^2 change between the regression including only lnphone
and the following one with the added birthrate is only 0.004. This is a suggestion of the
fact that the explicative power of birthrat is not much high.
c. Is the model significant in predicting lngdp? Explain.
Regression results indicate an overall model of two predictors (lnphone and birthrat) that
significantly predicts lngdp.
The R squared = .890, the Adjusted R squared = .888
d. What percentage of variance in lngdp is explained by the model?
The model accounted for 89% of the variance in lndgp, as it can be retrieved from the
e. Write the regression equation for lngdp.
lngdp = 6.878 + .663*(lnphone) – .013*(birthrat)
2. This question utilizes the data sets profile-a.sav and profile-b.sav,
You are interested in examining whether the variables shown here in brackets
[years of age (age), hours worked per week (hrs 1), years of education (educ), years
of education for mother (maeduc), and years of education for father (paeduc)] are
predictors of individual income (rincmdol). Complete the following steps to conduct
a. Using profile-a.sav, conduct a preliminary regression to calculate Mahalanobis
distance. Identify the critical value for chi-square. Conduct Explore to identify outliers.
Which cases should be removed from further analysis?
In order to calculate Mahalanobis distance, I conducted a preliminary regressio
Std. Error of
a. Predictors: (Constant), Highest Year of School
Completed, Father, Number of Hours Worked Last
Week, Age of Respondent, Highest Year of School
Completed, Highest Year of School Completed,
b. Dependent Variable: RESPONDENTS INCOME
The model summary indicates the general statistics of the regression where all the IVs
were included into the model
a. Dependent Variable: RESPONDENTS INCOME
b. Predictors: (Constant), Highest Year of School Completed, Father,
Number of Hours Worked Last Week, Age of Respondent, Highest Year
of School Completed, Highest Year of School Completed, Mother
The ANOVA table presents the model significantly predicts the dependent variable of
rincmdol, with the F-test for the overall significance telling us that at least one of the
predictors are statistically significant. F(5, 642) = 64.994, p<.001. Coefficientsa Unstandardized Coefficients B Std. Error -5.487 1.302 Model 1 (Constant) Age of .133 .016 Respondent Highest Year of School .507 .071 Completed Number of Hours Worked .142 .012 Last Week Highest Year of School .005 .074 Completed, Mother Highest Year of School .041 .055 Completed, Father a. Dependent Variable: RESPONDENTS INCOME Standardize d Coefficients Beta t -4.215 Sig. .000 .291 8.585 .000 .256 7.145 .000 .385 11.788 .000 .003 .066 .948 .030 .733 .464 The coefficient table indicates the coefficients that were used to predict the regression equation. Residuals Statisticsa Minimu Maximu m m Mean Predicted Value Std. Predicted Value Standard Error of Predicted Value Adjusted Predicted Value Residual Std. Residual Stud. Residual Deleted Residual Stud. Deleted Residual Mahal. Distance Cook's Distance Centered Leverage Value Std. Deviation N 4.16 24.16 13.64 3.080 648 -3.077 3.415 .000 1.000 648 .176 1.005 .398 .128 648 4.23 24.48 13.64 3.083 648 -15.499 -3.567 -3.583 13.759 3.166 3.188 .000 .000 .000 4.329 .996 1.001 648 648 648 -15.637 13.945 -.003 4.375 648 -3.616 3.211 -.001 1.003 648 .059 33.575 4.992 4.223 648 .000 .042 .002 .004 648 .000 .052 .008 .007 648 a. Dependent Variable: RESPONDENTS INCOME Case Processing Summary Cases Missing Valid N Mahalanobis Distance Percent 677 N 45.1% 823 Total Percent 54.9% N Percent 1500 100.0% The sample consisted of 1500 (823 missing values). Descriptives Statistic Mahalanobis Distance Mean 95% Confidence Interval for Mean Lower Bound Upper Bound 5% Trimmed Mean Median Variance Std. Deviation Minimum Maximum Range Interquartile Range Skewness Kurtosis Std. Error 4.9925522 .16121086 4.6760180 5.3090864 4.5041201 3.8432691 17.595 4.19458144 .05899 33.57526 33.51627 4.15036 2.310 7.910 .094 .188 The skewness statistics has a z-score of 2.310 /.094= 24.574. Based on this, we can conclude that the skewness is substantial and the distribution is non-normal. The kurtosis values are in line with that, 7.910/.188 = 42.074 shows there is no significance. Using a chi-squared table, critical value 22.458 was found, therefore, cases 406, 508, 18, 1129, and 351 exceeded that value so should be eliminated. The box plots is not normal and there are outliers at the highest end of the distribution. The critical value for chi-square is 22.458. Any cases with mahlabnobis>22.458 should
be eliminated from the regression analysis. Therefore, cases 406, 508, 18, 1129, and 351
were eliminated following this reasoning.
For all subsequent analyses, use profile-b.sav. Make sure that only cases where
MAH_1<22.458 are selected. b. Create a scatterplot matrix. Can you assume linearity and normality? The scatterplot matrix with the transformed variables displays elliptical shapes, suggesting that the variables are linear normally distributed. Tests of Normality Kolmogorov-Smirnova Shapiro-Wilk Statistic df Sig. Statistic df Sig. Age of Respondent Highest Year of School Completed .057 609 .000 .975 609 .000 .151 609 .000 .944 609 .000 Number of Hours Worked .184 609 Last Week Highest Year of School .270 609 Completed, Mother Highest Year of School .180 609 Completed, Father RESPONDENT .115 609 S INCOME a. Lilliefors Significance Correction .000 .960 609 .000 .000 .891 609 .000 .000 .964 609 .000 .000 .952 609 .000 The Shapiro-Wilk test is particularly useful for testing the non-normality of the variables. The null hypothesis of this test is that the variables are normally distributed. From the results, we can reject the null hypothesis for all the variables, concluding that none of them is normally distributed. From the plot we can see that the residuals of the regression do not cluster on a horizontal line; in fact, there is an even distribution above and below the reference. From this, it seems that there is a moderate violation of linearity and homoscedasticity, which however should not invalidate the analysis. d. Conduct multiple regression using the Enter method. Evaluate the tolerance statistics. Is multicollinearity a problem? Multicollinearity is not a problem because all tolerance statistics is greater than .1. Descriptive Statistics Std. Mean Deviation RESPONDENT 13.25 5.058 S INCOME Age of 39.45 11.547 Respondent Highest Year of School 14.25 2.587 Completed Number of Hours Worked 42.88 14.059 Last Week Highest Year of School 11.81 2.802 Completed, Mother Highest Year of School 11.65 3.862 Completed, Father N 609 609 609 609 609 609 Correlations Numbe RESPO Highest r of NDENT Year of Hours S Age of School Worked INCOM Respond Complet Last E ent ed Week Pearson Correlation RESPON DENTS INCOME Age of Responde nt Highest Year of School Comple ted, Mother Highest Year of School Comple ted, Father 1.000 .270 .335 .522 .036 .050 .270 1.000 -.017 .053 -.305 -.275 Sig. (1-tailed) Highest Year of School Complete d Number of Hours Worked Last Week Highest Year of School Complete d, Mother Highest Year of School Complete d, Father RESPON DENTS INCOME Age of Responde nt Highest Year of School Complete d Number of Hours Worked Last Week .335 -.017 1.000 .145 .321 .370 .522 .053 .145 1.000 .037 .049 .036 -.305 .321 .037 1.000 .578 .050 -.275 .370 .049 .578 1.000 . .000 .000 .000 .185 .109 .000 . .337 .097 .000 .000 .000 .337 . .000 .000 .000 .000 .097 .000 . .180 .112 N Highest Year of School Complete d, Mother Highest Year of School Complete d, Father RESPON DENTS INCOME Age of Responde nt Highest Year of School Complete d Number of Hours Worked Last Week Highest Year of School Complete d, Mother Highest Year of School Complete d, Father .185 .000 .000 .180 . .000 .109 .000 .000 .112 .000 . 609 609 609 609 609 609 609 609 609 609 609 609 609 609 609 609 609 609 609 609 609 609 609 609 609 609 609 609 609 609 609 609 609 609 609 609 Correlation table indicates number of hours worked has highest correlation (.522) and highest year of school completed (.355) is the second highest correlation. Also indicates both mom (.036) and dad (.050) have the lowest correlation. All variables were entered using the enter method. Model Summaryb Model 1 R .635a Std. Error of R Adjusted R the Square Square Estimate .404 .399 3.922 a. Predictors: (Constant), Highest Year of School Completed, Father, Number of Hours Worked Last Week, Age of Respondent, Highest Year of School Completed, Highest Year of School Completed, Mother b. Dependent Variable: RESPONDENTS INCOME ANOVAa Sum of Squares Mean Square Model df F Sig. 1 Regressio 6280.935 5 1256.187 81.677 .000b n Residual 9274.119 603 15.380 Total 15555.054 608 a. Dependent Variable: RESPONDENTS INCOME b. Predictors: (Constant), Highest Year of School Completed, Father, Number of Hours Worked Last Week, Age of Respondent, Highest Year of School Completed, Highest Year of School Completed, Mother The ANOVA table suggests that the model significantly predicts the dependent variable of income, with the F test of the overall significance telling us that at least one variable is useful in predicting the income, F(5, 603) = 81.677, p<.001. The coefficient table indicates the coefficients that were used to predict the regression equation. Collinearity Diagnosticsa Variance Proportions Di m en Conditi Age of si Eigen on (Cons Respo Model on value Index tant) ndent 1 1 5.716 1.000 .00 .00 2 .131 6.611 .00 .22 3 .082 8.342 .00 .19 4 .034 12.888 .03 .20 5 .024 15.366 .00 .13 Highest Year of School Comple ted .00 .00 .00 .07 .63 6 .012 21.772 .96 .26 .29 a. Dependent Variable: RESPONDENTS INCOME Residuals Statisticsa Minimu m Maximu m Mean Number of Hours Worked Last Week .00 .06 .85 .04 .02 Highest Year of School Complet ed, Mother .00 .03 .00 .26 .49 Highe st Year of Scho ol Comp leted, Fathe r .00 .17 .00 .80 .00 .03 .22 .01 Std. Deviation Predicted 3.26 23.15 13.25 Value Residual -15.487 8.673 .000 Std. Predicted -3.106 3.082 .000 Value Std. Residual -3.949 2.211 .000 a. Dependent Variable: RESPONDENTS INCOME N 3.214 609 3.906 609 1.000 609 .996 609 e. Does the model significantly predict rincmdol? Explain. The results indicate the model significantly predicts rincmdol. The explanation power is given by R square = .404 (not too high), Adjusted R squared = .399, F(5, 603) = 81.677, p <.001. f. Which variables significantly predict rincmdol? Which variable is the best predictor of the DV? The variables of age (B=.110, Beta=.252, t=7.485, p<.001), edu (B=.531, Beta=.271, t=7.818, p<.001), and hrs1(B=.169, Beta=.469, t=14.741, p<.001) significantly predict the DV. The variable of hrs1 is the best predictor of rincmdol as indicated by the beta weight and respective t and p-values. g. What percentage of variance in rincmdol is explained by the model? The model accounted for 40.4% of the variance rincmdol. h. Write the regression equation for the standardized variables. Income= -6.052 + .252 * age + .272 * educ + .469 * hrs + .017*maeduc + -.014*paeduc i. Explain why the variables of mother’s and father’s education are not significant predictors of rincmdol. Bivariate and partial correlation coefficients of these two variables with the DV are very low. Therefore, there seems to be not much evidence of these variables being important in explaining the DV. ... Purchase answer to see full attachment
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To describe a mathematical process or method used in your code, insert equations into your live script or function. Only text lines can contain equations. Insert an equation interactively — You can build an equation interactively by selecting from a graphical display of symbols and structures.
Was this helpful? If you have the Lucida Sans Unicode font installed check the font list in Word you are in luck. When you want to insert a symbol, click on the Insert menu and choose Symbol.
The line numbering commands are included in the ametsoc. If you are not using ametsoc. To correct the line numbering around display equations, you must add the following snippet of code to your.
Note: This page is a work-in-progress. Feedback and suggested improvements are welcome. Please join the discussion on moodle.
In the case of degrees of angular arcthe degree symbol follows the number without any intervening space, e. The addition of minute and second of arc units follow the degree units, with intervening spaces between the units but no spaces between the numbers and arc symbols, e. In the case of degrees of temperaturethree scientific and engineering standards bodies the International Bureau of Weights and Measuresthe International Organization for Standardization and the U.
If you or your project-sharing colleagues are using a pre version, you will need to follow the recommendations in the note under "Adding Special Characters and Formatting with the Object Properties Dialog", below. To create a text label, click the Text tool on the Tools toolbar, then click at the point on the graph, worksheet, etc. You are now in "in-place" edit mode.


I'm thinking of getting the mixing bundle and then later on upgrading to the total bundle, is that possible? If so, how much is it? Is it the difference price from $339 to $499? In other words, Is it..... $499 - $339 = $160 dollars for the upgrade....?
(Btw, I'm a student & I have an EDU account. So that's why I put those prices 50% off prices)


The University of Lviv is located in Ukraine, which is part of Europe.
It is a Catholic institution and offers degrees in theology, philosophy, law, medicine, dentistry, pharmacy, economics, engineering, mathematics, physics, chemistry, biology, psychology, history, geography, pedagogy, journalism, political science, sociology, international relations, linguistics, literature, philology, and many others.
Ukranian Catholic University was founded by the Ukrainian Greek Catholic Church in Lviv in
Ukranian Catholic University
1. Ukraine Catholic University (UCU) was established in Kyiv in 1869. In its early years, UCU was known as the Kyiv-Mohyla Academy. In 1920, it became a state institution. In 1992, the name was changed to Ukrainian Catholic University.
2. The first rector of UCU was Archbishop Myroslav Ivan Lubachivsky. He was appointed in 1869. His successor was Metropolitan Andrey Sheptytsky.
3. The current Rector of UCU is Bishop Volodymyr Kondratyuk.
4. The university has three faculties: theology, philosophy, and law.
5. There are four departments in the Faculty of Philosophy: Logic and Theory of Science, History of Philosophy, Ethics, and Political Sciences.
6. The Department of Law at UCU offers courses in civil law, criminal law, international law, public administration, and private law.
7. The Department of Theology offers courses in dogmatic theology, moral theology, pastoral theology, liturgical theology, and canon law.
8. The Department of Philosophy offers courses in logic, theory of science, history of philosophy, ethics, political sciences, and aesthetics.
9. The Department of Law offers courses in civil law and criminal law.
10. The Department of Theological Studies offers courses in dogmatic and pastoral theology.
11. The Department of Philosophy and Psychology offers courses in logic, epistemology, psychology, linguistics, and pedagogy.
12. The Department of Theoretical Physics offers courses in theoretical physics, mathematical physics, cosmology, and astrophysics.
13. The Department of Mathematics offers courses in algebra, geometry, trigonometry, calculus, probability theory, statistics, and numerical analysis.
14. The Department of Computer Science offers courses in computer science, information technology, programming languages, databases, and web design.