বাংলাদেশের সকল চাকুরির নিয়োগ বিজ্ঞপ্তি প্রকাশ করার পাশাপাশি আমরা এটাও বলে থাকি যে আপনি কিভাবে ঐ চাকুরি টি সহজেই পেতে পারেন। তাই নিয়োগ বিজ্ঞপ্তি গুলো ভালোভাবে পড়ার পাশাপাশি সাজেশন গুলো অনুসরণ করলে আশা করি আপনার উপকৃত হবেন। আমাদের ফেসবুক গ্রুপে যুক্ত হয়ে চাকুরির নিয়োগ সম্পর্কিত যেকোন প্রশ্ন করতে পারেন।
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By Linda J.S. Allen
KEY BENEFIT: This reference introduces various mathematical types for organic structures, and offers the mathematical conception and strategies beneficial in reading these types. fabric is prepared in line with the mathematical idea instead of the organic software. includes purposes of mathematical idea to organic examples in each one bankruptcy. makes a speciality of deterministic mathematical types with an emphasis on predicting the qualitative answer habit over the years. Discusses classical mathematical types from inhabitants , together with the Leslie matrix version, the Nicholson-Bailey version, and the Lotka-Volterra predator-prey version. additionally discusses newer versions, similar to a version for the Human Immunodeficiency Virus - HIV and a version for flour beetles. KEY MARKET: Readers seeking a pretty good heritage within the arithmetic at the back of modeling in biology and publicity to a large choice of mathematical types in biology.
Read or Download An Introduction to Mathematical Biology PDF
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The exponentially expanding quantities of organic info in addition to similar advances in computing energy are making attainable the development of quantitative, predictive organic structures types. This improvement may perhaps revolutionize these biology-based fields of technology. to help this alteration, the U.
Extra info for An Introduction to Mathematical Biology
However, if f is not continuous, the following example shows that an equilibrium can be globally attractive but not globally asymptotically stable. ) / / / // ...... ·>J': / ' : ' .... 7 /· : : x, x E (2, oo). / / // ·············>/ /: / : ' ' / / / r--r---- ................ 6), it is assumed that solutions are nonnegative; the initial conditions and fare restricted to the interval [O,a). For biological models, this is a reasonable assumption. It is often the case in biological models that zero is an equilibrium, f (0) = 0.
Two cases are consid x conve rges then b, > a if and b < a if 1 ates x 1 conve rge mono tonica lly to zero a < b. when brium equili ve positi a exist mono tonica lly to x. There does not 2 is sketch ed for x > 0. 4, the reprod uction curve l that if 0 < r < 3/4, Two cases are considered, 0 < r < 3/4 and r > 3/4. ;)/2 is locally t in the cobwebbing and if r > 3/4 it is unstable. 3. This latter example [Figur d. 2, f(f(x) = stable if 3/4 < r < 5/4. 5 Global Stability in First-Order Equations 47 46 Chapter 2 Nonlinear Difference Equations, Theory, and Examples x,+ x,+ 1 / L / / / / Globally attractive equilibria are locally attractive, and therefore globally asymptotically stable equilibria are locally asymptotically stable.
Igure . graphs the Liapu nov exponents of . b g 1/2 I x when . 1 Table in calculated value~ of the Liapunov exponent are given tlo~ condi shown only for the initial :l~o~~h. the Liapunov exponents =areA(xj) for Xj = f'·(xo). 99]. 18), we linearize the system Befo re we state the stability result for system abou t the equilibrium. X, y). f(x, y) yields expansion abou t the equilibrium for the function 1 Figure 2. 12 Liapunov 0 i:i <1) ;::l 0 ~ y) ( y - y_) f( x, y ) -_ f(-x, y_) + af(x, y) (x - x_) + af(x, ay ax 2 2 a2f(x, y) (y - y)2 a f(x, Y) (x - x) + + 2 + 2!
An Introduction to Mathematical Biology by Linda J.S. Allen


This template shows the daily linear regression line and standard deviation channels along with annualized % slope values for a selection of periods (5 days through 1 Year).
The 2 standard deviation channel upper and lower values are calculated along with a value indicating where the close price is in relation to the bands.
The Annualized slope % is a value which shows where the linear regression line will be in 1 year if it continues on its current trajectory. By annualizing this value it is possible to compare stocks to show which are increasing or decreasing at a greater rates. Also by showing a selection of different periods for linear regression slopes side-by-side it is possible to see which timeframes have the steepest slopes. Therefore this template can be used to uncover a lot of different scenarios. For instance if you want to see stocks that have an upward slope over a 1 year period, a downward slope over a 3 month period and an upward slope over a 10 day period it is easy to do by sorting the columns in the appropriate order.
By default the results are sorted by the 252 Day (1 Year) slope of the linear regression line in descending order which means that stocks that have the best trajectory in the longer time frame rise to the top of the list.


Title: Threshold estimation for jump-diffusions under small noise asymptotics
Authors: Yasutaka Shimizu - Waseda University (Japan) [presenting]
Mitsuki Kobayashi - Waseda University (Japan)
Abstract: The focus is on parameter estimation of stochastic differential equations driven by a Wiener process and a compound Poisson process as small noises. The goal is to give a threshold-type quasi-likelihood estimator and show its consistency and asymptotic normality under new asymptotics. One of the novelties is that we give a new localization argument, which enables us to avoid truncation in the contrast function that has been used in earlier works and to deal with a wider class of jumps in threshold estimation than ever before.


GirlsGetMath@Dearborn is a five-day mathematics program at the University of Michigan – Dearborn that is open to 15 high school students who live in the Metro Detroit area. We will explore topics such as cryptography, the mathematics of voting, image processing, prime numbers and factoring, and fractals. Students will learn through interactive lectures, games and daily computer lab activities.
In Summer 2021 the program will be virtual, meeting July 26 – 30, 9 am – 12 pm.
There is no fee for those selected to participate, but students are expected to commit to attending all five days.
For more information and to apply, please visit https://sites.google.com/umich.edu/ggmdearborn


In these first few weeks of school, I wonder how many parents have heard complaints from their children about math, and how many have responded with something about how bad they used to be at math. Adults can have very strong and negative feelings about math.
We remember our first experiences, and if we struggled with math, we may still see it as something awful. We know it has importance, but we are still not fans! Teachers call it “math anxiety,” and recognize that when parents have a negative opinion about math it directly influences their child’s opinion.
The moment we say something about “being bad at math, too,” to our children, it is like a green light for them to just give up and quit trying. The truth is, human brains are capable of learning anything, even math!


TBILISI, GEORGIA: Teo, 19, and Mako, math students, were hanging out in the center of Tbilisi on an early May evening.
I meet lots of law, finance, marketing & programming students in the ex-USSR, but very few math students.
For Mako at least, it is probably in her genes to pursue this science: both her father & grandfather were math teachers.
She intends to follow in their footsteps and teach as well. Teo said she would likely become a teacher as well.


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CPM Course 1: General Math Period 5– Text PIN Number: RSH33
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1. Compute, by hand (and show your work), the mean,
and standard deviation for the following data:
a) Use Excel to generate a random variable, with 31 observations, a mean of 10 and a standard deviation of 1.
To create a random variable in excel, use "data", "data analysis" and "random number generator".b) use Excel to compute the mean, variance (use the function 'var') and the standard deviation (use the function 'stddev') for the generated data in (a).
The number of variables should be 1, number of random numbers should be 31, distribution should be normal, mean should be 10 and standard deviation should be 1. NOTE: In "Random Seed" type in any combination of three numbers. Then specify the output range for the random numbers.
If you don't see 'data analysis' you'll have to install it, Excel may not have installed it automatically.
c) construct a 95% and 99% confidence intervals for the computed mean. Use table B-1 in the textbook to find the (two-sided) t-value needed to construct the confidence intervals and make sure you use the appropriate degrees of freedom.
d) Use the t-test, given in the textbook on p.563, to test each of the following null hypothesis:
i) Ho: mean=0Can (each) null hypothesis be rejected at the 5% significance level (use a two-sided test)?
ii) Ho: mean=5
iii) Ho: mean=10


GraphPad Prism Crack is a non-linear freehand application to measure the regression unit and analysis from any graph. It refers to the entered data from your tabular notation also with master key points. The preferred analysis and graphing solutions are purpose-built for scientific research. Join the world’s leading scientists and discover how you can use GraphPad Prism Crack to save time, make more appropriate analysis choices, and elegantly graph and present your scientific research. Unlike spreadsheets or other scientific graphing programs.
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Paired or unpaired t-tests. Reports P values and confidence intervals.
Nonparametric Mann-Whitney test, including confidence interval of difference of medians.
Kolmogorov-Smirnov test to compare two groups.
Wilcoxon test with a confidence interval of the median.
Perform many t-tests at once, using False Discovery Rate (or Bonferroni multiple comparisons) to choose which comparisons are discoveries to study further.
Ordinary or repeated measures one-way ANOVA followed by the Tukey, Newman-Keuls, Dunnett, Bonferroni or Holm-Sidak multiple comparison tests, the post-test for trend, or Fisher’s Least Significant tests.
Many multiple comparisons tests are accompanied by confidence intervals and multiplicity-adjusted P values.
Greenhouse-Geisser correction so repeated measures one-way ANOVA does not have to assume sphericity. When this is chosen, multiple comparison tests also do not assume sphericity.
Kruskal-Wallis or Friedman nonparametric one-way ANOVA with Dunn’s post-test.
Fisher’s exact test or the chi-square test. Calculate the relative risk and odds ratio with confidence intervals.
Two-way ANOVA, even with missing values with some post-tests.
Two-way ANOVA, with repeated measures in one or both factors. Tukey, Newman-Keuls, Dunnett, Bonferroni, Holm-Sidak, or Fishers LSD multiple comparisons testing main and simple effects.
Three-way ANOVA (limited to two levels in two of the factors, and any number of levels in the third).
Kaplan-Meier survival analysis. Compare curves with the log-rank test (including the test for trend).
Calculate min, max, quartiles, mean, SD, SEM, CI, CV,
Mean or geometric means with confidence intervals.
Frequency distributions (bin to histogram), including cumulative histograms.
Normality testing by three methods.
One sample t-test or Wilcoxon test to compare the column mean (or median) with a theoretical value.
Skewness and Kurtosis.
Identify outliers using Grubbs or ROUT method.
Calculate slope and intercept with confidence intervals.
Force the regression line through a specified point.
Fit to replicate Y values or mean Y.
Test for departure from linearity with a runs test.
Calculate and graph residuals.
Compare slopes and intercepts of two or more regression lines.
Interpolate new points along the standard curve.
Pearson or Spearman (nonparametric) correlation.
Analyze a stack of P values, using Bonferroni multiple comparisons or the FDR approach to identify “significant” findings or discoveries.
Receiver operator characteristic (ROC) curves.
Deming regression (type ll linear regression).
Simulate XY, Column, or Contingency tables.
Repeat analyses of simulated data as a Monte-Carlo analysis.
Plot functions from equations you select or enter and parameter values you choose.
The area under the curve, with confidence interval.
Subtract baseline (and combine columns).
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My name is Greg Winn I am a web developer, specializing in web application development. Take a look at some of my projects, then drop me a line.
View older articles.
Most of my projects can be followed on Github (@gregwinn)
Recently I needed to calculate a bunch of LED current limiting resistor values for different colored LED’s. In order to quickly do this I created a simple TI BASIC program that runs on my TI-Nspire CX CAS calculator based on the math used to calculate the value.
This very simple math problem will give you the current limiting resistor value for any LED!
# # R = The Resistor value # R = (VCC - Forward Voltage) / Forward Current
Let me know if you have any questions or edits.


4 edition of Starmaths found in the catalog.
by Collins Educational
Written in English
|Statement||Suzanne Edwards, Cherrie Wild, Susan Warner. Orbit 5.|
|Contributions||Wild, Cherrie., Warner, Susan.|
|The Physical Object|
|Number of Pages||48|
Starmaths: Orbit 2 by Suzanne Edwards, Cherrie Wild, Susan Warner starting at $1, Starmaths: Orbit 2 has 1 available editions to buy at Half Price Books Marketplace. STAR Maths Online, Liverpool, New South Wales. K likes. S.T.A.R. Maths online is the new and smarter way for your child to achieve results!5/5(14).
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Stuart J. Murphy's Mathstart: Level 2 books. MathStart stories use visual learning strategies to teach important mathematical concepts. If you’re looking for an easy and fun way to boost reading time for kids, these free Star Wars-Inspired Coloring Bookmarks are the way to go!. Let your Star Wars fans customize their own bookmarks for a stellar reading accessory. Great for parties, library, classroom, homeschool, and family fun 🙂.
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STAR MATHS. PROYECTO. TEMARIO. 1ºESO. 2ºESO. NIVELES. More. En esta página web quiero motivar a nuestros alumnos de 1º y 2º de ESO para que aprendan que las matemáticas son divertidas y útiles. La web es una herramienta para ayudar a los alumnos a disfrutar con las matemáticas.
"Que la fuerza os acompañe". STAR Maths Online - Student. Splash page: Links to MathStart books by level. Click on each level to read more about the books. Renaissance Star Maths is a computer-adaptive baseline test that provides in-depth reports for screening, planning teaching, and monitoring progress.
Book a free online demonstration of Star Assessments. Please use the form below to arrange an online demonstration of. This practice test book is the perfect preparation tool for California's STAR Mathematics test.
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The bliss and healing meditation workshop is coming up and it makes me realize I have a lot to learn. Stillness, for one. One thing that has always helped me is using the beads. I also use rosaries, but what I just learned today which is kinda sweet is that 'mala' means rose - or rosary, rose garland from above and on.
I s'pose one can find coincidences in everything - and most folks don't find math to be much fun - but when I started looking into the magic number 108 I have to admit being enlightened and amused. Words like, "108 is considered an abundant and semiperfect number. A semiperfect number is either perfect or abundant. An abundant number that is not a semiperfect number is a weird number."
The fact is there is a lot of mystery around the number 108, the abundant and semiperfect number. In Japan on New Years, the bell is chimed 108 times representing the 108 earthy temptations we must surpass to find a way to nirvana. In Hindu, the deities have 108 names. Actually, there are a few folks that document an exhaustive list of reasons 108 is an auspicious number... It's kinda interesting. Check it out!


Angela Mendoza is a passionate, sincere, intelligent, professional and premier Realtor from Los Angeles, California. With a Bachelor’s in Mathematics and a Master’s in Information Technology, Angela’s analytical mind makes her the consummate problem solver.
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Analisis Faktor-Faktor Yang Mempengaruhi Penyaluran Dana Bank Syariah
Studi kasus PT Bank Syariah Mandiri
This study aims to determine the effect of NPF, ROA and BOPO on Fund Distribution. This research was conducted using the method of collecting and processing financial report data for the 2005-2020 period of Bank Syariah Mandiri based on a predetermined sample using a saturated sample. This study used a data test tool, namely the classical assumption test and the data were analyzed using multiple linear regression analysis. The results of this study are as follows: Partially the Non-Performing Financing Ratio has a significant effect on the distribution of funds, the significance value is -2.971 <0.012. Return on Assets has a significant effect on the distribution of funds with a significance value of -2.361 <0.036. Operational Expenses Operational income has no significant effect on the distribution of funds, the significance value is 1.050> 0.314. Simultaneously, the effect of NPF<ROA, and BOPO has a significant effect on Fund Distribution with a significance value of 0.012<0.05. The value of Adjusted R2 is 0.479, which means that the three independent variables affect the dependent variable by 0.479 (47.9%) and the rest is influenced by other variables.


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Hard to believe, but Youngest started college this week. He resisted greatly having his picture taken, but I played the "mom" card and won out. You only have one "very first day of college" in your college career.
Tuesday evening, after he finished his second day of calculus (what 17 yr old takes a class like that his first semester?!) and he was bouncing off the wall with excitement. He tried to explain how awesome it was, but the words math and awesome do not belong in the same sentence in my world. This is the kid who solves a Rubics cube, in close to a minute, and says it's simple because it's just an algorithm... Who is this kid??? He tried to explain how fun and challenging it was to solve the problem below, but my mind couldn't fathom any of it.


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Write in ascending order Worksheet 3 Write in ascending order Worksheet 3. In the Worksheet You have to write numbers in ascending order. The worksheet will improve your child’s number counting abilities. Grade = Subject = Also Check: Simple Deer coloring page Worksheet Template Reverse counting Number Fill in the blanks Worksheet
Write Less than or Grater than Worksheet 2 Write Less than or Grater than worksheet 2. This worksheet will help kids to practice math ability and enhance number sense. Grade = Subject = Also Check: Add 10 To the Number and find the Sum 1 Fill in the blanks with missing Alphabets


3 edition of Lectures on probability theory found in the catalog.
Lectures on probability theory
Ecole d"Г©tГ© de probabilitГ©s de Saint-Flour (23rd 1993)
|Statement||P. Biane, R. Durrett ; editor, P. Bernard.|
|Series||Lecture notes in mathematics -- 1608, Lecture notes in mathematics (Springer-Verlag) -- 1608.|
|Contributions||Biane, P., Durrett, Richard, 1951-, Biane, P., Durrett, Richard, 1951-|
|LC Classifications||QA3 .L28 no. 1608|
|The Physical Object|
|Pagination||210 p. :|
|Number of Pages||210|
PROBABILITY THEORY 2 LECTURE NOTES These lecture notes were written for MATH at Cornell University in the Spring semester of They were last revised in the Spring of and the schedule on the following page re ects that semester. These notes are for File Size: KB. If anybody asks for a recommendation for an introductory probability book, then my suggestion would be the book by Henk Tijms, Understanding Probability, second edition, Cambridge University Press, This book first explains the basic ideas and concepts of probability through the use of motivating real-world examples before presenting the theory in a very clear way.
A free online version of the second edition of the book based on Stat , Introduction to Probability by Joe Blitzstein and Jessica Hwang, is now available at and is complementary to the Stat lecture videos on YouTube. Lectures on Probability Theory and Mathematical Statistics is an excellent text, because it is clearly written, easily readable, covers a lot of ground, and explains things intuitively. Melissa Herston, J // This book helps me a lot. It is easy to understand and it is very good for self study as well.
We introduce sample spaces and the naive definition of probability (we'll get to the non-naive definition later). To apply the naive definition, we need to be able to count. So we introduce the. LECTURE NOTES on PROBABILITY and STATISTICS Eusebius Doedel. TABLE OF CONTENTS SAMPLE SPACES 1 Events 5 The Algebra of Events 6 Axioms of Probability 9 Further Properties 10 Counting Outcomes 13 Permutations 14 Combinations 21 CONDITIONAL PROBABILITY 45 In Probability Theory subsets of the sample space are called Size: 1MB.
Romance and the rock
At home with hurricanes.
land rights of individuals among the Myakyusa
Report & Accounts.
Modelling storm period fluctuations in suspended sediment
Sky blue, Vassily Kandinsky
Chester mystery plays
U.S. Geological Survey ground-water studies in Arkansas
Journal of Landsboroughs Expedition from Carpentaria, in Search of Burke And Wills
The book is a collection of 80 short and self-contained lectures covering most of the topics that are usually taught in intermediate courses in probability theory and mathematical statistics. There are hundreds of examples, solved exercises and detailed derivations of important results/5(8).
Lectures on Probability Theory and Statistics nd Edition by E. Bolthausen (Author) ISBN ISBN Why is ISBN important. ISBN. This bar-code number lets you verify that you're getting exactly the right version or edition of a book Cited by: 5. This book is a collection of lectures on probability theory and mathematical statistics.
It provides an accessible introduction to topics that are not usually found in elementary textbooks. It collects results and proofs, especially on probability distributions, that are hard to find in standard references and are scattered here and there in more specialistic books/5(18).
This volume contains two of the three lectures that were given at the 33 rd Probability Summer School in Saint-Flour (July).
Amir Dembo’s course is devoted to recent studies of the fractal nature of random sets, focusing on some fine properties of the sample path of random walk and Brownian : Tadahisa Funaki, Amir Dembo. Lectures on Probability Theory and Mathematical Statistics is an excellent text, because it is clearly written, easily readable, covers a lot of ground, and explains things intuitively.
After going through this book and looking at some other comparable titles, I have to come to the conclusion that this is an excellent text on the topic of Probability Theory and Mathematical Statistics/5.
Learning probability from him is like learning from Aristotle. Varadhan has two other similar volumes one covering stochastic processes the other into the theory of large deviations (though older than this current text).
The book on Stochastic Processes should be paired with this by: This book contains work-outs of the notes of three hour courses of lectures which constitute surveys on the concerned topics given at the St.
Flour Probability Summer School in July The first course, by D. Bakry, is concerned with hypercontractivity properties and their use in semi-group theory, namely Sobolev and Log Sobolev inequa.
there are many excellent books on probability theory and random processes. However, we ﬂnd that these texts are too demanding for the level of the course.
On the other hand, books written for the engineering students tend to be fuzzy in their attempt to avoid subtle mathematical concepts. As a result, we always end up having to complement the.
Book Features. The 2nd Edition includes two new chapters with a thorough coverage of the central ideas of Bayesian and classical statistics. Develops the basic concepts of probability, random variables, stochastic processes, laws of large numbers, and the central limit theorem.
Illustrates the theory. This book is of interest to PhD students in probability and statistics or operators theory as well as for researchers in all these fields. The series of lecture notes from the Saint-Flour Probability Summer School can be considered as an encyclopedia of probability theory and related fields.
Lectures on Probability Theory and Mathematical Statistics Second Edition Marco Taboga. Probability and Stochastic Processes. This book covers the following topics: Basic Concepts of Probability Theory, Random Variables, Multiple Random Variables, Vector Random Variables, Sums of Random Variables and Long-Term Averages, Random Processes, Analysis and Processing of Random Signals, Markov Chains, Introduction to Queueing Theory and Elements of a Queueing System.
Probability Theory and Statistics Lecture notes. The aim of the notes is to combine the mathematical and theoretical underpinning of statistics and statistical data analysis with computational methodology and practical applications.
These are the lecture notes for a year long, PhD level course in Probability Theory that I taught at Stanford University inand The goal of this courseis to prepareincoming PhDstudents in Stanford’s mathematics and statistics departments to do research in probability theory. More broadly, the goal of the text.
This volume contains lectures given at the Saint-Flour Summer School of Probability Theory during the period 10th - 26th July, These lectures are at a postgraduate research level. They are works of reference in their domain.
This volume contains lectures given at the Saint-Flour Summer School of Probability Theory during the period 8thth July, We thank the authors for all the hard work they accomplished. Their lectures are a work of reference in their domain. The School brought together 85 participants, 31 of whom gave a lecture concerning their research work.
Introductory lecture on Probability Theory: The Logic of Science by E.T. Jaynes. Aubrey Clayton, March e-books in Probability & Statistics category Probability and Statistics: A Course for Physicists and Engineers by Arak M. Mathai, Hans J.
Haubold - De Gruyter Open, This is an introduction to concepts of probability theory, probability distributions relevant in the applied sciences, as well as basics of sampling distributions, estimation and hypothesis testing.
This book contains two of the three lectures given at the Saint-Flour Summer School of Probability Theory during the period August 18 to September 4, Keywords Probability theory Rang Stochastic calculus interacting particle system interacting particle systems non commutative stochastic calculus percolation quantic probability.
The lectures present areas of modern probability theory that are current areas of research. The material is accessible to undergraduate students with a modest background in probability. This collection of lectures will be an excellent supplement to any intermediate probability course Journal of the American Statistical Association.
Description: This lecture is a review of the probability theory needed for the course, including random variables, probability distributions, and the Central Limit Theorem. Instructor: Dr. Choongbum Lee.The course material is contained in the union of the following online texts for first-year graduate probability courses: S.R.S.
Varadhan's lecture notes; Amir Dembo's lecture notes (PDF) Rick Durrett's book at CiteSeer (PDF) or at Amazon and here is a recently updated version (PDF) from Durrett's web page.
Noel Vaillant's A series of specialized books on Probability theory and Sta-tistics of high level. This series begin with a book on Measure The-ory, its counterpart of probability theory, and an introductory book on topology. On that basis, we will have, as much as possible, a coherent Size: 1MB.


Giant Mechanical "Brain" Does Intricate Sums
h EDP order
CSIRO Problem In Computer Network
The Sydney Morning Herald, 8 August, 1944
NEW YORK, Aug. 7. From our Staff Correspondent, A.D. Rothman.
The gift cost 250,000 dollars (£A78,121) to build and eight years to develop, and is the work of Commander Howard Aiken, United States Naval Reserve, who in civilian life is Mathematics Professor at Harvard.
A sort of mechanical brains trust, the machine is in the hands of the Navy for the
duration of the war and serving in the war effort, but with the return of peace,
it is expected to facilitate explorations in pure mathematics and science hitherto
hindered by intricate and time-
It solves a problem in 5.8 seconds that it takes an hour for a human to do. In one case, it achieved in 19 hours what it took four persons three weeks to do even with the aid of ordinary mechanical calculators.
It works out trigonometric functions in 55 seconds.
It contains error-
When a problem is fed into the calculator in coded tape form, it will carry out the solution to 23 significant figures, consulting logarithmic and other functional tables which lie in the machine or are coded on tapes.
The operator of the machine need not be a trained mathematician, but mathematicians must prepare the problems by using a code book, so that the operator may punch the code holes in tape to feed the problem to the machine.
In the field of atomic physics, radio research, investigation of the ionosphere (the layer in the upper atmosphere which reflect radio waves), actuarial work, optics and electronics, the benefits of the invention are expected to immense.
The machine has already exposed eleven errors in one mathematical formula which has been standard for certain calculations for years.


Which bug is the biggest? Which bug is the longest? It’s time to find out as all the bugs in Ladybug’s garden line up for the best bug parade! This fun book written by Stuart J. Murphy and illustrated by Holly Keller introduces size comparison in its simplest form.
Kids will love the story and the illustrations. Parents and educators will love how the story and pictures make understanding the math concepts a breeze—as well as the concrete examples of how math works. The book contains activities for adults to do with kids to extend math into their own lives. Math = Fun!
MathStart is an award-winning series by Stuart J. Murphy that teaches math through stories and visual models. Young readers find the stories engaging and relatable, because each story revolves around practical applications of the math concept being presented and features lively art from top-notch illustrators.
Charts and other visual representations help children understand how the math works and promote deeper comprehension. This unique combination of stories, illustrations, and visual models helps teachers and parents in the teaching of math and provides all children with the opportunity to succeed.
The 63-book series is divided into three levels with 21 books in each. The math concepts taught in MathStart books conform to state and national standards. Level 1 is Pre-K–Kindergarten; Level 2 is Grades 1–3; Level 3 is Grades 2–4. The series follows math topics across grades so there is a foundational path to learning that runs through the levels.
1 in stock


When you create calculations in Smartabase, you're often able to write your own equations to calculate the result you're interested in. Some calculations don't allow you to use your own equations (for example, linked calculations), but for the calculation types that do, you have a wide range of built-in functions that simplify the process of writing equations.
The functions that are available for use depend on the calculation type. To see the full list of functions for the specific calculation field you're working with, select the Available functions drop-down at the bottom of the Calculation tab and open the tooltip to see details about each function.
This article covers functions that you can use in:
The calculations above can be used within tables, and you will find that many of the functions described here are useful for table calculations as well (calculations about the contents of a table in a form). You can find more information about additional functions that are used exclusively in table calculations in the article on setting up table calculations.
This article also doesn't cover the functions that are specially designed for history calculations, because historical functions are included in the article on building history calculations.
Since functions can be used across a variety of calculation types, this article organizes functions according to their purpose:
- Numeric functions
- Statistical functions
- Reference functions
- Logical functions
- Text functions
- Date and time functions
Note that Smartabase functions are not yet internationalized and therefore use British English, which means you must use non-American spelling in functions like textsummarise.
Numeric functions are for mathematical operations. You can use them across all calculations as long as the arguments for the functions are numeric.
- abs: returns the absolute value of a number.
abs(2) = 2
abs(-2) = 2
- ceiling: rounds a number up.
ceiling(12.3) = 13
- floor: rounds a number down.
floor(12.7) = 12
- gt: determines if the first value is greater than the second value.
gt(10, 5) = true
- gteq: determines if the first value is greater than or equal to the second value.
gteq(10, 5) = true
gteq(10, 10) = true
- ln: calculates the natural logarithm of a number.
ln(9) = 2.19722...
- log: calculates the logarithm (base 10) of a number.
log(12) = 1.07918...
- lt: calculates if the first value is less than the second value.
lt(5, 10) = true
- lteq; calculates if the first value is less than or equal to the second value.
lteq(5, 5) = true
lteq(5, 10) = true
- mod: calculates the remainder when dividing one number by another.
mod(9, 1) = 0
- pow: raises the first value to the power of the second value.
pow(2, 3) = 8
pow(2, 4) = 16
- safe: returns a number value or zero. This can be useful if fields that are part of a calculation might be empty but you still want a result.
When Strength rating contains 3, safe(Strength rating) = 3
When Strength rating is empty, safe(Strength rating) = 0
- sqrt: calculates the square root of a value.
sqrt(9) = 3
- sum: calculates the sum of all values.
sum(1, 5, 61) = 67
- trunc: returns the closest whole number. It is possible to use trunc to round to the nearest x (x could be 0.5, 2.5, 5, 10, etc.). To do so, divide the number by x and then multiply it by x again as in the second and third examples.
trunc(5.3) = 5
trunc(5.4/0.5) * 0.5 = 5.5
trunc(12.97738/10) * 10 = 10
Statistical functions are useful when you want to do descriptive statistical analysis. You can use these functions across all calculation types.
The sprint testing examples below assume that the following values are entered for number fields named Sprint 1 through to Sprint 5.
Sprint 1 = 4.434
Sprint 2 = 4.597
Sprint 3 = 4.561
Sprint 4 = 4.482
Sprint 5 = 4.545
- count: counts the number of items given.
count(5, 3, 2, 9, 19, 24) = 6
count("football", "cricket", "swimming") = 3
- max: calculates the maximum value of a range.
max(39, 41, 40, 28, 34) = 41
max(Sprint 1, Sprint 2, Sprint 3, Sprint 4, Sprint 5) = 4.597
- min: calculates the minimum value of a range.
min(120, 124, 119, 134, 129) = 119
min(Sprint 1, Sprint 2, Sprint 3, Sprint 4, Sprint 5) = 4.434
- mean: calculates the mean value of all values within a range.
mean(Sprint 1, Sprint 2, Sprint 3, Sprint 4, Sprint 5) = 4.5238
- median: returns the median value of a range.
median(Sprint 1, Sprint 2, Sprint 3, Sprint 4, Sprint 5) = 4.545
- nthmax: returns the nth largest value of a range, with n being any positive whole number.
nthmax(2, 10, 45, 12, 15) = 15
nthmax(4, 10, 45, 12, 15) = 10
- nthmin: returns the nth smallest value of a range, with n being any positive whole number.
nthmin(2, 10, 45, 12, 15) = 12
nthmin(4, 10, 45, 12, 15) = 45
- sem: calculates the standard error of the mean from a range of values, which is the standard deviation divided by the square root of the number of values.
- stddev: calculates the standard deviation for a range of values.
stddev(Sprint 1, Sprint 2, Sprint 3, Sprint 4, Sprint 5) = 0.065197393
stddev(Lift 1, Lift 2, Lift 3)
- var: calculates the variance of a range of values.
var(Sprint 1, Sprint 2, Sprint 3, Sprint 4, Sprint 5) = 0.0042507
Reference functions are essentially look up operations, meaning that they are used to find values using a certain criterion. They can be used in all calculation types as long as the output is consistent with what the calculation type expects. For example, when using a reference type function in a simple (numeric) calculation, the result of the calculation should be a number, not text or a date.
- contains: determines if the first value contains the second value.
contains("Three green pairs of shoes", "green") = 1
contains("Three green pairs of shoes", "red") = 0
- firstnonzero: returns the first value from a range which is not zero:
firstnonzero(0,0,3,2,4) = 3
- firstpositive: returns the first positive value from a range:
firstpositive(-2,-3,2,6,7) = 2
- firstvalue: returns the first value from a range:
firstvalue(4,2,6,7,9) = 4
- index: returns a specified item from a range:
index(3, "blue", "orange", "purple", "red", "violet", "yellow") = purple
- lastnonzero: returns the last value from a range that is not zero:
lastnonzero(7,2,5,6,0) = 6
- lastpositive: returns the last positive value from a range:
lastpositive(4,6,1,3,-5) = 3
- lastvalue: returns the last value from a range:
lastvalue( 4, 7, 2, 6) = 6
- and: evaluates n number of statements and returns 1 if all of them are true and 0 if at least one of them is false.
and(5 < 6, 2 > 0, contains(“abc”, “a”), 2 = 2) = 1
and(2 > 1, 3 < 7, 0 > 4) = 0
- anyempty: checks whether any of the fields being referenced are empty. If any fields are empty, the function returns a 1, otherwise 0.
When any of the fields referenced are empty, anyempty(Strength, Weakness, Opportunity, Threat) = 1
When none of the fields referenced are empty, anyempty(Strength, Weakness, Opportunity, Threat) = 0
- if: checks whether a statement is true or false and returns pre-defined values for each state.
When Score contains 96, if(Score > 80, "Pass", "Fail") = Pass
When Score contains 31, if(Score > 80, "Pass", "Fail") = Fail
- isempty: checks whether all of the fields being referenced are empty. If all fields are empty, the function returns a 1, otherwise 0.
When all four fields referenced are empty, isempty(Strength, Weakness, Opportunity, Threat) = 1
When any of fields referenced contain data, isempty(Strength, Weakness, Opportunity, Threat) = 0
- or: evaluates n number of statements and returns 1 if at least one of them is true or 0 if none of them are true.
When Fatigue contains 5, or(Fatigue > 3, Energy < 3, Motivation < 3) = 1
When Fatigue contains 2, Energy contains 4, Motivation contains 5, or(Fatigue > 3, Energy < 3, Motivation < 3) = 0
- charat: returns the nth character of the specified text, with 0 being the first character.
When Ticket Code contains 234-4532-029450-A, charat(Ticket Code, 1) = 3
- concatenate: combines all items specified into a single text string, which is useful for summarizing important information.
When Sets contains 3 and Reps contains 12, concatenate(Sets, “x”, Reps) = 3x12
- customtextsummarise: combines all items specified into one text string, using the first item as the divider.
customtextsummarise(" --- ", Motivation, Energy, Fatigue) = High --- Low --- Moderate
- option: if option fields have scores, Smartabase will use the score in calculations. You can use the option function to use the text result of an option field for the calculation.
When the option called Extreme (scored as 5) for Rating is selected, option(Rating) = Extreme
- replace: replaces all occurrences of the second value in the first value with the third value. Note that the arguments for the replace function are case sensitive.
replace("Example", "e", "@") = Exampl@
- replaceall: replaces any occurrences of the third or subsequent values in the first value with the second value.
replaceall("one two three four five six", "zero", "one", "three", "five") = zero two zero four zero six
- split: splits a specified text using the second value. The third value specifies which occurrence of the second value will be used to split the text. You cannot split a value with a period.
When Ticket Code contains 234-4532-029450-A, split(Ticket Code, "-", 2) = 029450
- splitfirst: this function works the same way as as split but there is no need to specify a third value. It automatically returns the first segment of the text, like using a a split function with 0. You cannot split a value with a period.
When Ticket Code contains 234-4532-029450-A, splitfirst(Ticket Code, "-") = 234
- splitgreaterthan: splits a string of text using the second value and returns everything after the occurrence specified by the third value. You cannot split a value with a period.
When Ticket Code contains 234-4532-029450-A, splitgreaterthan(Ticket Code, "-", 1) = 4532 029450 A
- splitlast: same as splitfirst but in this case the function returns the last value. You cannot split a value with a period.
When Ticket Code contains 234-4532-029450-A, splitlast(Ticket Code, "-") = A
- splitlessthan: same as splitgreaterthan but in this case it returns the everything before the third value. You cannot split a value with a period.
When Ticket Code contains 234-4532-029450-A, splitlessthan(Ticket Code, "-", 2) = 234 4532
- substring: specify the start position (second argument) and number of characters (third argument) to return from a field specified in the first argument.
When Ticket Code contains 234-4532-029450-A, substring(Ticket Code, 0, 3) = 234
- textsummarise: combines all items specified into one string of text separated by commas.
When Color contains Blue, Shape contains Square and Size contains Small, textsummarise(Color, Shape, Size) = Blue,Square,Small
- whitespacetextsummarise: combines all items specified into one string of text separated by blank spaces.
When Color contains Blue, Shape contains Square and Size contains Small, whitespacetextsummarise(Color, Shape, Size) = Blue Square Small
Date and time functions
- date: returns a date value using the default date format for the Smartabase site.
When Graduation Date contains 05/31/2021 and the site default date format is mm-dd-yyyy, date(Graduation Date) = 05-31-2021
- dateformat: converts a date value to the specified format.
When Graduation Date contains 05/31/2021, dateformat(Graduation Date, "DDDD") = Monday
- duration: converts milliseconds to a duration in the specified format.
When Result contains 1326000, duration(Result, "hh:mm:ss") = 00:21:06
- weekstart: tells you which week of the year a date falls within. However, you must specify which day you consider the week to start on (Sunday = 0, Saturday = 6), which week of the year you want to start counting from (0 - 52) and which week of the year you want the start week to be.
When Graduation Date contains 05/31/2021, weekstart(Graduation Date, 0, 1, 1 ) = 22


Published at Sunday, 27 September 2020. Reading Worksheets. By Lavern Brunel.
Patterns and sequencing and basic addition and subtraction should follow on from counting and number recognition. By the time your child is starting kindergarten or school, they should be able to count to 20 with ease, write numbers, do simple addition sums, and have some understanding of patterns and sequences. Even if they are attending preschool, extra practice at home will help them improve their math.
There are many opportunities to teach your child how to count. You probably already have books with numbers and pictures, and you can count things with your child all the time. There are counting games and blocks with numbers on them, wall charts and a wide variety of tools to help you teach your child the basic principles of math. Mathematics worksheets can help you take that initial learning further to introduce the basic principles of math to your child, at a stage in their lives where they are eager to learn and able to absorb new information quickly and easily.
Ask yourself these questions when preparing a handout whether it is for the first day of school or just a plain ordinary lesson on teaching reading strategies. What is the aim of the handout? Will I grade the handout? Will I go over the handout in class or collect it? How much percentage will I give for handouts for the final grade?Is my handout well prepared? Do students have enough information to tackle the subject matter of the handout? Are the instructions crystal clear? Do I want the students to finish the handout at home or during class time?
Any content, trademark’s, or other material that might be found on the Indieiosfocus website that is not Indieiosfocus’s property remains the copyright of its respective owner/s. In no way does Indieiosfocus claim ownership or responsibility for such items, and you should seek legal consent for any use of such materials from its owner.
Copyright © 2021 Indieiosfocus. All Rights Reserved.


Today we did some tally mark practice by counting down how many days we have left of school. Here is my daughters paper.
She decided to draw a chart so she could color in the box for the day. We have 39 days left of school! So excited! My 7 year old son is having a hard time getting his work done lately. Now that he knows he only has 39 days left he found a new surge of energy to do his best. How do you practice tally marks with your kids?


I have to confess it was Graeter’s that reminded me that Pi Day was coming up.
I saw the sign, and realized that, since I’m both a baker and a geek, I could do better. My family had a Pi Day feast.
For our entrée, we had Pizza Pi.
Desert was a French Silk Pi.
While we ate, my wife and I explained the significance of pi to my daughter. We figured that this nine inch pie pan had an area of 63.6 square inches. Estimating it as being an inch-and-a-half tall, and our pi has a volume of 95 cubic inches. That’s a lot of pie (and very geeky).


Learn various math skills while playing games.
This is a variety of puzzles and games for all ages that relate to some of the topics that are covered in math. You'll find games for those who want to enhance their math skills and games for students who simply enjoy the subject and like working with numbers. Some games and puzzles are challenging while others are just fun to play and feature cupcakes, pizza, animals and other cartoons. There are puzzles based on logic and those that are for younger children who are just beginning to understand math concepts like addition and subtraction.


Argyll Scott is helping the client looking for Head of Data Scientist and directly report to CEO. This role is responsible for predictive modeling to evaluate scenarios and make predictions on future outcomes in order to solve highly complex business problems and support decision making, Analyzes very large data sets in real time databases and develops and implements mathematical approaches.
- Develops complex algorithms and statistical predictive models and determines analytical approaches and modeling techniques to evaluate scenarios and potential future outcomes
- Performs analyses of structured and unstructured data to solve multiple and complex business problems. utilizing advanced statistical techniques and mathematical analyses and specialized expertise in the organization and/or industry
- Applies analytical rigor and statistical methods to analyze large amounts of data, using advanced statistical techniques
- Manages large and complex analytical projects from data exploration, model building, performance evaluation and testing
- Behaves as mentor to junior team members to provide technical advice
- Collaborates with business partners to develop technical /business approaches and new or enhanced technical tools
- Interacts with internal and external peers and management to share highly complex information related to areas of expertise and/or to gain acceptance of new or enhanced technology / business solutions
- Manages and responsible for the successful delivery of the algorithms, statistical models and reporting tools to meet business needs, Acts as the analytic team lead for large and complex projects involving multiple resources and tasks, providing individual mentoring in support of company objectives
- Bachelor / Master or equivalent work experience in Mathematics, Statistics, Computer Science, Business Analytics, Economics, Physics, Engineering, or related discipline
- Moreover 10 years experience or more years of progressively complex related experience
- Strong skills to effectively communicate and negotiate across the business and in the external health care environment Excellent analytical and problem solving skills
- Strong organizational, management and leadership skills
- Deep knowledge of advanced analytics tools and languages to analyze large data sets from multiple data sources
- Solid understanding of health care industry, products, and systems
- Demonstrates proficiency in all areas of mathematical analysis methods, machine learning, statistical analyses, and predictive modeling and advanced in-depth specialization in some areas
- Demonstrates strong ability to communicate technical concepts and implications to business partners.
- Fluent in English and Thai
Argyll Scott Asia is acting as an Employment Agency in relation to this vacancy.


In the latest Building Bridges article for NCETM (link below), I discuss the merits of some well-known methods for long multiplication:
NCETM – Long multiplication by lattice method
Let me know what you think and also check out my previous post on times tables as these skills are the cornerstone of long multiplication.
If you don’t have an NCETM login, here’s the full version of the article:
Building Bridges – Issue 129
In the last issue, we discussed strategies for developing pupils’ fluency with their times tables. Once these key facts are secure, how can we improve our pupils’ fluency with procedures that use them, in particular “long multiplication”? We discussed last year (in Issue 119), the grid method, and advocated it as a powerful and long-lasting model that helps pupils extend their conceptual understanding from area and the multiplication of numbers to the multiplication and factorization of algebraic expressions. A challenge to the grid method is that it’s not very efficient for multiplying two 3-digit or larger numbers, and that it requires pupils to be confident with place value: it’s a good stepping stone from concrete to abstract multiplication, but it’s often not the best method when actually you want to calculate the product of two numbers. The traditional “long multiplication” algorithm is more efficient than the grid method, but it too expects confident understanding of place value: in a KS3 class with pupils with low prior attainment, that may be an unrealistic expectation, at least when they first join the school.
An algorithm which takes away the stress of being forced to consider place value (which will result in errors if zeros are forgotten or misunderstood and hence misplaced), is to use what’s often called the Lattice Method. We must point out here, for historical accuracy, that this is sometimes incorrectly referred to as Napier’s Method. Napier did devise a clever system of multiplication using blocks (known as Napier’s Bones) built on the Lattice Method; this is a story well worth investigating further. A strong advantage of the Lattice Method is that it requires, and hence reinforces, understanding of and fluency with times tables up to 9, and most of the place value thinking is ‘below the surface’. Pupils, especially those with low prior attainment, therefore often find it an easier algorithm to implement correctly than the grid method or classic “long multiplication”; this builds their confidence, which is hugely important. The lattice method helps pupils get the right answer without getting bogged down by other concepts which may not be securely understood, or which may be understood but in practice can still produce errors.
The beauty of the algorithm is in its simplicity: let’s take an example and calculate 23 × 385 = 8855. We multiply the digits pairwise, and record the answer to each separate multiplication using tens and units above and below the diagonal lines:
It can also be used effectively to multiply two decimals such as 1.58 × 1.6:
Of course, the decimal point can be inserted after calculating first the integer product 158 × 16, and then considering the scale factors between the original factors, the integers, the integer product, and hence the original product. There are short videos on YouTube showing lattice multiplication and decimal lattice multiplication.
The caveat to the lattice model is no doubt obvious, but let us state it nonetheless: the lattice method is a good algorithm, but it’s not a good model for multiplication – in particular, it doesn’t generalise naturally from the concrete to the abstract. Therefore, once pupils are confidently calculating products using a lattice, they must then also calculate them using a grid and a “long multiplication”, so that they develop understanding of and fluency with these more powerful models.
Also, this is a good context for developing pupils’ reasoning: they can consider a rich question such as “what’s the same and what’s different?” about the three methods as they are written out on the page – comparing the lattice above with
In particular, they should look at the “partway” calculations – 6900, 1840 and 115 in the grid method and 1155 and 7700 in the long multiplication. Do these also occur, perhaps hidden, in the lattice? If not, is just a miracle that the answers are all the same (we hope!)?


The course covers the basic computations involved in working with whole numbers, fractions, decimal’s, percent’s, squares, and other topics.
A study of basic mathematics, enabling the student to gain math proficiency required for vocational programs. Topics included are decimals, fractions, calculator use, and measurement.
This course covers properties and operations of numbers, equations, computation with positive and negative numbers, and graphs.
Properties of the real number system, factoring, linear and quadratic equations, polynomial and rational expressions, inequalities, systems of equations, exponents, radicals, functional notation, rational equations and absolute value equations.
Relations and functions, equations and inequalities, complex numbers; polynomial rational, exponential and logarithmic functions and systems of equations. Graphing calculators are required.
Systems of linear equations and inequalities, matrices, linear programming mathematics of finance, elementary probability, and descriptive statistics.
Angle measure trigonometric and inverse trigonometric functions, trigonometric identities and equations, parametric polar coordinates, and general application.
Equations and inequalities, polynomial, rational, exponential, logarithmic, trigonometric and inverse trigonometric functions, trigonometric identities and equations and applications.
Systems of linear equations, row operations, echelon form, matrix operations, inverses determinants, vectors in Euclidean space, vector spaces, subspaces, homogeneous systems, linear independence, rank, and dimension.
Limits, derivatives, integrals, exponential and logarithmic functions, and applications. Graphing calculator required.
Limits, continuity, differentiation, Mean Value Theorem, integration, Fundamental Theorem of Calculus, and applications.
Applications and techniques of integration, polar equations, parametric equations, sequences and series, power series and application.
An introduction to statistical methods of gathering, presenting and analyzing data. Topics include probability and probability distributions, confidence intervals, hypothesis testing, and linear regression and correlation.
Multivariate and vector calculus including partial derivatives, multiple integration and its applications, line and surface integrals, Green’s Theorem and Stoke’s Theorem.
Solution of elementary differential equations by elementary techniques, Laplace transforms, systems of equations, matrix methods, numerical techniques and applications.


An ACUTE (all angles are acute) triangle contains three acute angles (each angle of an acute triangle is less than 90 degrees).
The acute angle is the small angle which is less than 90° but more than zero degrees
sum of the angles of an acute triangle is always 180 degrees.
An acute triangle may be isosceles,scalene or equilateral.
The right triangle has one 90 degree angle and two acute (< 90 degree) angles
An equilateral triangle is a specific type of acute triangle where the three angles have an equal measure of 180°/3 = 60°.


Your browser does not currently recognize any of the video formats available. Click here to visit our frequently. In this video, I show the formula of expected value, and compute the expected value of a game. The final. A quick introduction to expected value formulas. Expected Value Formula. Stephanie Glen. Loading.
Formula for expected value - für unerfahrene
Printer-friendly version Expected Value i. Half of the time, the value of the first roll will be below the EV of 3. The amount by which multiplicativity fails is called the covariance:. Sophisticated content for financial advisors around investment strategies, industry trends, and advisor education. This version of the formula is helpful to see because it also works when we have an infinite sample space. Add together the six probability-value calculations to find the EV for the overall game. It is possible to construct an expected value equal to the probability of an event by taking the expectation of an indicator function that is one if the event has occurred and zero otherwise.
Formula for expected value Video
Decision Analysis 2: EMV & EVPI - Expected Value & Perfect Information You should either list these or create a table to help define the results. Formula Basic Expected Value Formula The basic expected value formula is the probability of an event multiplied by the amount of times the event happens: Of course, calculating expected value EV gets more complicated in real life. In classical mechanics , the center of mass is an analogous concept to expectation. The values for all six possible outcomes are as follows: Copy this code to embed the article on your site: Identify all possible outcomes. By the previous corollary,. Over the long run of several repetitions of the same probability experiment, if we averaged out all of our values of the random variable , we would obtain the expected value. Working With Discrete Random Variables This video walks through one example of a discrete random variable. Petersburg Paradox has been stumping mathematicians for centuries. By definition of Lebesgue integral,. Using the probability distribution for number of tattoos, let's find the mean number of tattoos per student. They are 1, 2, 3, 4, 5 and 6. Given a large number of repeated trials, book of ra kostenlos online spiel average iphone apps aktualisieren the results will gmx logiin approximately equal to the expected value. To calculate the standard deviation we first must calculate the variance. X is the number of heads which appear. So your values for X http://nypost.com/tag/gambling/ 0,1,2 and 3. Let X be a discrete random variable taking values eye of magic 1game twist app 2 , The moorhuhn spielen gratis a player can expect paysafe codes list win or lose if they were to place a bet on the same odds many times over, calculated through a simple equation multiplying your probability of winning with the amount you could formula for expected value per bet, parsip subtracting the probability of losing multiplied by the amount lost per bet. Probabilty Distribution for Number of Tattoos Each Student Has in a Population of Students Tattoos 0 1 2 3 4 Probability. According to the model, one can conclude that the amount a firm spends to protect information should generally be only a small fraction of aufladen gutschein expected loss i. They solved the treue testen kostenlos in french pen pals free computational ways but their results were identical because their computations were based on the same fundamental principle. Thus, over time you should expect to everestpoker echtgeld money. You might want to save your money! The logic of EV can be used to find solutions to more complicated problems. In probability theory , the expected value of a random variable , intuitively, is the long-run average value of repetitions of the experiment it represents. Essentially, the EV is the long-term average value of the variable. The expected value EV is an anticipated value for a given investment. Add up the values from Step 1:


williamghunter.net > Biography continued
Statistical Design of Experiments Project to teach high school students. Bill's connection: In 1984, Bill Hunter was a principal organizer and speaker at the Woodrow Wilson Foundation summer institute on Quantitative Literacy in Princeton, NJ. There he taught the teachers about DOE and the Statistical Design and Analysis of Experiments.
In 1959 he graduated from Princeton University. Next, he attended the University of Illinois for a year before enrolling as the first doctoral student in statistics at the University of Wisconsin - Madison. For the following 20 years he taught at the University of Wisconsin - Madison Statistics Department and elsewhere. View the Feb 1986 CV for Bill Hunter and Bill Hunter in Memoriam.
George Box and Bill Hunter on Videotape
"Practice and Theory; Some Personal Experiences," George Box and Bill Hunter (1982), 43 minutes from the American Statistical Association Distinguished Lecture Series (broken link was removed)


Then my friend Steven Carter released his viz titled "The Adoption Gap" (and subsequently won Viz of the Day) where he took my picture idea to the next level with his household grid. Using formulas, he was able to set a grid, and then show a gradually filled in house to represent the number of adoptions needed.
AND THEN Chris Luv released his viz explaining INDEX() and SIZE(), two incredibly valuable table calculations in tableau to determine size and position of a point. Using INDEX and SIZE, he was able to completely recalculate row and column values on the fly, removing a lot of constraints Steven and I had come up with. His final viz was so good, it made me rethink my entire design.
Having been inspired by a number of sources, I present a fourth option (very close to Chris' solution but with a slight tweak). I have build a sample viz that shows how to use formulas and table calculations to autoscale and autoalign shapes (or visualizations as Chris will show) to a grid based on how many values are available. Check out the final result below.
HOW TOIn my original sports viz, I was unaware that Tableau will do the sizing and arranging work for you if you have rows and columns that the images will fit in. So here's how to use a unique ID column to auto generate the links we need
1) Create 'Y Axis' Field
So what is going on here? The idea is that as the number of objects to display is usually best represented in equal rows and columns. Thus, the number of rows we want (represented on the Y axis) should be the square root of the objects/dimension values. The INDEX() -1 offsets the values so they continue to line up instead of shifting out.
2) Create 'X Axis' Field
INDEX() - (INT((INDEX()-1)/ROUND(SQRT(SIZE())))) * ROUND(SQRT(SIZE()))
This one is a bit more complicated, but is to continue to hit on the idea of displaying equal number of rows and columns. So with the 'Y Axis' figuring out a bucket for values for the row, the X axis needs to reassign the ID for the value so that the rows start over successfully.
So what this formula is doing is taking the current index value, subtracting the y axis bucket multiplied by the bucket value to always reestablish the new set of rows.
3) Build sheet and assign shapes
The setup is as follows
a) [ID] goes in the details
b) 'X Axis' goes on the columns shelf, convert to discrete
c) 'Y Axis' goes on the rows shelf, convert to discrete
d) 'Y Axis' and 'X Axis' should be addressing every field (see second screenshot for the how to)
|a), b), & c)|


Ph.D. in Mathematics, University of Missouri, Columbia, 2015
B.S. in Mathematics, University of Missouri, Columbia, 2007
Dr. Hesam Oveys is a Clinical Assistant Professor of Mathematics at the Courant Institute of Mathematical Sciences at New York University.
Dr. Oveys began teaching in 2007 as a Graduate Instructor at the University of Missouri while working toward his Ph.D and joined the NYU faculty in 2016. His teaching experience stretches from summer enrichment courses for high schoolers to advanced courses in number theory and probability for undergraduates and recent graduates. At NYU, Dr. Oveys teaches and coordinates a variety of math courses, including Calculus 1-3, Discrete Mathematics, Statistics, Linear Algebra, and Quantitative Reasoning courses.
He is also a Faculty Advisor for math majors, trains new TAs to prepare them for the classroom, and mentors first year post-docs.


A robust knowledge of biostatistics is important for designing and conducting high-quality radiology research. As the complexity of research increases, there is a growing and urgent need for academic radiologists to acquire fundamental skills in biostatistical methods. Each Webinar was previously recorded live and can be accessed below using YouTube.
This two-part webinar covers individual statistical comparisons (both parametric and non-parametric). Content includes characterizing the nature of your data, selecting the right statistical test, and obtaining p-values. Tests that investigators can perform themselves, as well as pitfalls and caveats in obtaining and interpreting p-values, are highlighted. Examples of covered statistical tests, along with numerous case examples, include paired and unpaired t-tests, the Wilcoxon and Mann Whitney tests, Fisher's exact test, and the McNemar test.
This webinar provides an overview of the basic aspects of probability and statistics needed to critically appraise and perform research. Fundamental concepts of probability and statistics are covered to provide a foundation for further study.
This lecture defines and describes the basics of building, applying, and interpreting an ROC curve.
The RAHSR/RRA Webinar Series is supported by a Venture Fund Grant from the AUR Research and Education Foundation


Treena Basu is an Associate Professor of Mathematics in the Department of Mathematics at Occidental College. Basu was previously a visiting assistant professor at Ithaca College in Upstate New York. She received her PhD. in Applied and Computational Mathematics from the University of South Carolina.
Basu's research interests span a broad range of fields in Applied Mathematics: Numerical Analysis, History of Statistics, and Data Science. The interdisciplinary nature of Basu's work, allows her to employ a range of mathematical tools for real-world physical modeling which includes numerical approximation through finite difference, finite volume and multi-grid methods, and machine learning algorithms.
France Hoffman is an Assistant Professor in Computing and Mathematical Sciences at Caltech and the AIMS-Carnegie Research Chair in Data Science at AIMS Rwanda. She completed her PhD at the Cambridge Centre for Analysis (CCA) Doctoral Training Centre, University of Cambridge and Imperial College London. She was previously a Bonn Junior Fellow with the Hausdorff Center for Mathematics at Rheinische Friedrich-Wilhelms-Universität Bonn, Germany. Currently, she is a member of the Institute of Applied Mathematics (IAM), and she serves on the Steering Committee of the Transdisciplinary Research Area 1 “Modeling” at University of Bonn, as well as serving as Program Director of the new Doctoral Training Program in Data Science (DTP-DS) at Quantum Leap Africa (QLA), AIMS Rwanda.
Hoffman's research interests lie at the interface of model-driven and data-driven approaches, including mathematical tools for numerical PDEs and Data Analysis.
Qing Nie is a Chancellor's Professor of Mathematics and Developmental & Cell Biology, affiliated with the Department of Biomedical Engineering, at the University of California, Irvine. He is also the Director of the NSF- Simons Center for Multi-scale Cell Fate Research. He completed his PhD in Mathematics at the Ohio State University, Columbus, Ohio.
Nie's research interests include computational systems biology, cell fates, multi-scale biology, and tools for analyzing single-cell RNA-sequence data, scientific computing, and computational mathematics.
Hayden Schaeffer is a Professor in the Department of Mathematics at UCLA, and previously was an Assistant Professor in the Department of Mathematics at CMU. He received an NSF CAREER Award and an AFOSR Young Investigator Award. Previously, he was an NSF Mathematical Sciences Postdoctoral Research Fellow, a von Karmen Instructor at Caltech, a UC President’s Postdoctoral Fellow at UC Irvine, and a Collegium of University Teaching Fellow at UCLA. His education includes a Ph.D. and Masters in mathematics from UCLA and a B.A. from Cornell University.
Schaeffer's research interests include data science, sparse models, math modeling, and imaging sciences.


In the following example, a prime divisor of the number 10117 is to be calculated. Let only the prime numbers < 49 = 72 be known. These prime numbers are stored in a file "FileP1.txt". The remainders or complements of the primes 2, 3, 5 and 7 at 49 are calculated. I have defined the complement as compi = pi − remainderi, i.e. the number 49 for example and pi = 5 then is 49 mod 5 = 4 and the next multiple of 5 is 50. Therefore here the complement is 1. The complements at 49 for the primes 2, 3, 5 and 7 are 1, 2, 1 and 7. The next prime is 11 and its square is 121. The difference 121 - 49 = 72 and therefore a fill area created for these elements has 73 elements. The even numbers are ignored. Therefore only the 1., 3., 5., . . . of the filling area calculated. This fill area is first emptied, i.e. all these elements are set to zero. Then the filling of the filling area beginsThe 3 has the complement 2 and fills the fields 3, 6, 9, . . . , the 5 has the complement 1 and fills the fields 2, 7, 12, . .. . Accordingly the 7 fills the fields 8, 15, 22, . . . . After all fields are occupied, for the sake of completeness the first element with 7 and the last element with 11.
Now the evaluation of the filling area begins. All fields that have not been occupied correspond to the prime numbers in the range 49 to 121. They are stored in the file "FileP2.txt". The complements at 73 (in the filling range) or 121 are calculated. It can be obtained as follows: If the upper limit of 73 is exceeded by a multiple of a prime number during filling, then the complement results from the difference of this number - 73. With these complements start in the following fill aerea. To do this, the next prime number is read from "FileP1.txt". It is the 13. This filling range should accommodate the elements from 121 to 169 = 132. It has 49 elements. The elements of the fill area are set to zero and then with the help of the complements calculated at 121 the new fill area is filled. In addition to the complements of the numbers 3, 5, 7, the 11 is now added. It has the complement 11 (or 0) at 121. Again, the prime numbers result from the elements that have not been occupied. In the file "FileP2.txt" these prime numbers are added.
This procedure continues - initially until all prime numbers from "FileP1.txt" are used up. Figure 1 shows the squares of the prime numbers and the associated complements up to 472, i.e. up to 2209. Per line, the squares of the prime numbers and the complements of the prime numbers at these squares are listed. Now "FileP1.txt" is supplemented by the values from "FileP2.txt". After that, the file "FileP2.txt" is deleted and filled with the new prime numbers that are determined with the continuation of the procedure.
Table 1 lists the complements of the prime numbers in the squares of the prime numbers. The square 169 is smaller than the searched number 10177, which is to be broken down into prime dividers. Therefore, the next filling range is calculated. It is first emptied and filled with the prime numbers with the help of the complements. The resulting prime numbers are added to the prime numbers present in the "FileP2.txt" file. Continue with this method until all prime numbers from "FileP1.txt" are processed. This is the case with the prime number 47. Thus, the prime numbers from 53 to 2207, the largest prime number less than 472, are stored in file "FileP2.txt".
If you continue in this way, you finally reach the number range in which pi2 ≤ 10117 ≤ pi+12. This is the range between 972 and 1012. Here, the filling area is evaluated more thoroughly. The result is shown in Table 2. Each element from the fill area corresponds to a number between pi2 and number range in which pi2 ≤ 10117 ≤ pi+12. This is the range between 972 and 1012. Here, the filling area is evaluated more thoroughly. The result is shown in Table 2. Each element from the fill area corresponds to a number between pi2 and pi+12.
Only the ungraded numbers are listed. Under "Index" the index from the fill area is displayed. Under "Number" the respective number between the prime number squares is listed and with "Prime factor" a prime factor is displayed. It is the smallest prime factor of the corresponding number. As you can see, 10117 has a prime factor of 67. With a small change in the algorithm, the largest prime factor < pi+1 (here < 101) or all prime factors < 101 can also be displayed. Each factor is then listed only once. This algorithm has also been used to find the prime numbers up to 10201. The prime square and complements of the prime square 10201 are stored in a file. This has the advantage that you can use it when searching for a prime divider of a larger number can fall back on these values and does not have to start again at 49. Of course, you can save it anywhere (preferably with a square of a prime number).


25 is between zero and one, we know the function is decreasing. Before graphing, identify the behavior and create a table of points for the graph. Function Grapher is a full featured Graphing Utility that supports graphing two functions together. Now there&39;s many ways to graph this. Graphing points on coordinate plane worksheets are meant to simplify the process. Out of the box stunning transitions when changing data, updating colours and adding datasets. x yy = -x2 y = x2 + 3 y = x2. But do graph plotting transitions try to make your graph look reasonable.
Functions can get very complex and go graph plotting transitions through transformations, such as flips, shifts, stretching and shrinking, making the usual graphing techniques difficult. Function Transformations Just like Transformations in Geometry, we can move and resize the graphs of functions Let us start with a function, in this case it is f (x) = x2, but it could be anything: f (x) = graph plotting transitions x2. To use the graphing functionality, you&39;ll need to have graphviz and/or pygraphviz installed: To generate graphs with the package graphviz, you need to install Graphviz manually or via a package manager. graph plotting transitions Try plotting the circle with the equation in the graph plotting transitions form x 2 + y 2 = 5 2 see here ". Desmos offers best-in-class calculators, digital math activities, and curriculum to help every student love math and love learning math. We were also able to see the points of the function as well as the initial value from a graph.
Use "x" as the variable like this:. The graph of y = -x2 is the reflection of the graph of y = x2 in the x-axis. Before trying to build an animated plot with gganimate, make sure you understood how to build a line chart with R and ggplot2. There are three basic methods of graphing linear functions. When you move a graph horizontally graph plotting transitions graph plotting transitions or vertically, this is called a translation.
D3’s interpolators support both primitives, such as numbers and numbers embedded within strings (font sizes, path data, etc. Tweening can be controlled via easing functions such as “elastic”, “cubic-in-out” and “linear”. To use the graphing functionality, you&39;ll need to have graphviz and/or pygraphviz. 38 I&39;ve noticed that if a state machine has a state that can transition to the same state (e.
() that provides a frame variable. Vtrs 0 P 2 T V T graph plotting transitions P G. Squeezing or stretching a graph is more of a "transformation" of the graph. Find out if your company is using Dash Enterprise. I ask this because graph plotting transitions the result of the graph does differ when you shift first and then reflect v.
A feasible transition is a transition whose probability of occurring is greater than zero. Directed Graph A directed graph, or digraph, shows the states in the chain as nodes, and shows feasible transitions between states as directed edges. $&92;endgroup$ – Aniket Oct 24 &39;16 at 23:39 $&92;begingroup$ Alway reflect before shifting. Level up on the above skills and graph plotting transitions collect up to 500 Mastery points Start quiz. conducting-superconducting transition in metals at low temperatures. A translation in which the size and shape of a graph graph plotting transitions of a function is not changed, but the location of the graph is. Create a table of points as in Table 3. The graph of this function is shown below with a WINDOW of X: and Y: (-2, 4, 1).
show_auto_transitions (default False): Shows auto transitions in graph plotting transitions graph; show_state_attributes (default False): Show callbacks (enter, exit), tags and timeouts in graph; Transitions can generate basic state diagrams displaying all valid transitions between states. More Graph Plotting Transitions images. Up next for you: Unit test. The canvas for drawing plot images has a coordinate system in which the origin (0,0) is always located at the top, leftmost corner of the graph plot area. This trigonometry video tutorial explains how to graph tangent and cotangent functions with transformations and phase shift. Yes the positive square root is the default. So let me get my little scratch pad out.
In my research I use it before surgery and after surgery &39; but it can be used in any situation where you have a change from &39; one state to another &39; &39; transition_flow This should be a matrix with the size of the transitions. Graphing a circle anywhere on the coordinate plane is pretty easy when its equation appears in center-radius form. These sheets are a great help graph plotting transitions for those who are just learning to plot points on a graph.
For each value of the variable, a step on the chart will be drawn. So it&39;s y is equal to 5x squared minus 20x plus 15. First-order and second-order phase transitions (II) G Ttrs ΔGtrs 0 Second-order phase transition graph plotting transitions T V Ttrs T S Ttrs T H Cp-S T G P V P G T -continuous (S and V do not jump at transition) Ttrs T Ttrs T Strs 0 Htrs graph plotting transitions 0 P P dT dH C e. Before graphing, identify the behavior and key points on the graph. When we take a function and tweak its rule so that its graph plotting transitions graph is moved to another spot on the axis system, yet remains recognizably the same graph, plotting graph plotting transitions we are said to be "translating" the function.
Then, connect those four points graph plotting transitions with a nice, round circle. The transitionPlot function aims at illustrating the transition between classes. Let ; Carefully inspecting the equation f(x) tells us that. Graphing a function is not as simple as creating a table and plotting those graph plotting transitions points. It has the unique feature that you can save your work as a URL (website link). Customize the graph plot area of intensity, mixed signal, and waveform graphs by drawing a background, foreground, or middle image in the plot area.
I&39;d like to plot a transition graph plotting transitions matrix, but I want 2 columns with every state. Example: The graph of y = x2 + 3 is the graph of y = x2 shifted upward three units. 2 The transition probability color plot An example of transition probability color plot is displayed in Figure 1. The dotted line is Y = D = 2 and serves as the horizontal axis.
We&39;re asked to graph the following equation y equals 5x squared minus 20x plus 15. See more videos for Graph Plotting Transitions. Graph the function y = 2 x graph plotting transitions 2 − 5. Graph a linear function using transformations We previously saw that that the graph of a linear function is a straight line. Graphs of inequalities Get 3 of 4 graph plotting transitions questions to level up!
If your young learner needs a confidence boost, graphing points on a coordinate plane worksheets can help in class or as homework. Plot a default digraph of graph plotting transitions the Markov chain. It discusses how to also use th. But you do need to know how to do function transformations, because there are ways to ask the questions that don&39;t allow you to.
" Absoultely brilliant got my kids really engaged with graphs. You can just take three values for x and figure out what the corresponding values for y are and just graph those three points. In other words, every point on the parent graph is translated left, right, up, or down. My matrix is: > R 0 0. Transitions can generate basic state diagrams displaying all valid transitions between states. graph plotting transitions The idea is to add an graph plotting transitions additional aesthetics called transition_. graph plotting transitions Drawing to the Graph Plot Area. &39; A transition plot &39; &39; This plot purpose is to illustrate how graph plotting transitions states change before and &39; after.
), and compound values. It is based on the same data as used to construct the graph plotting transitions transition matrices shown in Table 1. plotting Speci cally, plotting the plot is a ‘choropleth’ representation of a 30-by-30 graph plotting transitions transition graph plotting transitions matrix using color progression to visualize. You can always "cheat", by the way, especially if you have a graphing calculator, by quickly graphing y = (x –and verifying that it matches what you&39;ve drawn. 6 32-bit transitions 0. Transitions gradually interpolate styles and attributes over time. Usage To plot a function just type it into the function box. All you do is plot the center of the circle at (h, k), plotting and then count out from the center r units in the four directions (up, down, left, right).
To plot the graph of a function, you need to take the following steps − Define x, by specifying the range of values for the variable x, for which the function is to be plotted. The original intent was to show how self-administered the Charnley classification behaves before and after surgery. Transum: Glad to hear they were so engaged. The left tail of the graph will increase without bound, and the right tail will approach the asymptote y = 0.
Improve plotting your math knowledge with free questions in "Translations: graph the image" and thousands of other math skills. s if you reflect first, and then do the shifting. Graphing a function is not as simple as creating a table and plotting those points. The point plotted has coordinates and serves as a “starting point” for a sine graph shifted units to the right. If we start with y = x 2 and multiply the right side by 2, it stretches the graph vertically by a factor of 2.
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