In lesson #3, we marked all the color areas on the graph paper with a corresponding yarn blending number which we also tied to our threading card for reference, like a paint by number painting. (Oh no, don’t glaze over yet!) To determine the amount of yarn we’ll need, first let’s do it mathematically so we know the ballpark amount. This technique is really easy, and I can in a moment tell you how much yarn any given backing will require by multiplying the number of knots that can be made across a horizontal row times the number of rows in the rug.
With this Monet’s Bridge design, I have hemmed two (2) 34″ wide rayon and linen backings which each can hold 84 knots across the row. 84 x 2 = 168 knots across the row. In this backing there are about 21 rows per foot and this is a 4-foot tall rug, I happened to hem the backing in a way that allows for 82 knotable rows. So our graph is designed to be 168 knots x 82 rows. (Calculator, please.) 168 x 82 = 13,776 knots in the entire rya.
With this number, you can figure out lots of information.
- If you make 150 knots per hour, it will take you 91 hours to knot a rya this size
- If you make a loop (pile) that is about 1 1/2″ long, you will get about 325 knots from a skein. 13,776 knots divided by 325 knots per skein = 43 skeins needed for this 4′ x 6 ‘ rya.
- If you wanted a 2″ long pile, you would get about 300 knots from a skein. So how many skeins would YOU need to knot a 4′ x 6′ rya? Calculators welcome.
- If you don’t like complicated stuff, and you hate math, you could simply say, “OK, my rug needs 43 skeins of yarn, I will order a mixed bag of the colors I need–maybe only 30 skeins, then I’ll see what I run out of, and order more of that at that time.” I am fine with that. It gets you started, and by the time you need more yarn, you’ll have a good idea of future needs.
If this doesn’t really interest you, don’t bother reading any further! But if you are one of the many folks who has asked for this and can not wait for my illustrated book to come out, brace yourself…. here comes the real math with no apologies.
For each color combination threading you have created on your threading card, count–or estimate–the number of knots in your rug of each of those color combinations. I usually count by 10’s or square inches on the graph which have 70 knots.
Now I agree, that is a lot of counting and numbers. Now we’ll make sense of them. The last column on the right (below) tell us how many skeins of each pure color we need to order to make our Monet rug. Notice only 1/4 skein is needed in certain lesser-used colors. Lots of 1/2 skeins. As my grandparents did, I also am happy to split skeins for rya rug makers. It can save you a lot of money to only buy 1/4 instead of a full skein of every color.
I pulled all the yarn from the storage shelves for making this rug. Here is what the pile of supplies looks like. So now, all that is left is to have Bill stop by to reacquaint himself with rya rug making, give him a mini-lesson until he feels totally comfortable with the project that will take him about 90+ hours, then home he goes to work on his rya at his leisure. I can’t wait to see the design become reality. I’m sure Claude Monet is thrilled too.
PS. As I was writing this all down for you I was a little mortified that I had chosen such a detailed design with which to explain the yarn calculations. I’ll go with a more basic design next time. My book will have it MUCH more basic to start, but this degree of difficulty is good to know if you want to design your own from paintings for example.
Questions? This is a good place to ask.


The number sequence strategy as a method of playing Keno
The number sequence strategy is less risky than the Martingale strategy. On one hand, the method does not promise to return the money you lose right away but on the other hand, it is much more flexible. The followers of this method act as follows: first, they fix the amount of money they want to win and then they fix the time i.e. how fast they want to achieve this goal. Every time they win (not necessarily the fixed amount), they reduce the set of numbers by 2 numbers. Every time they lose, they add another number. The strategy is based on the fact that players all the time bet on the same numbers until they win. This system is particularly popular among players all over the world in combination with the methods of D’Alemebert and Martingale described above.


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Bachelor of Science in Elementary Education with specialization of Mathematics at Philippine Normal University - Agusan Campus
Tutor the pupils here in school I want to tutor because I want to impart my knowledge and I want to earn money for my child because I am a single mother. Math, English, Algebra Tutor the pupils here in school I want to tutor because I want to impart my knowledge and I...
Graduated the Degree Bachelor of Secondary Education Major in English at the University of Southeastern Philippines-Bislig Campus
-Has teaching experience in a Tutorial Learning Center -Has passed the Licensure Examination for Teachers and Civil Service Eligible -I want to become a tutor because I want to extend help to students who are in need of help prior to their learning abilities at school....


I’d love to show you how to use my Fierce Feathered Star block in this lap sized layout! It’s kind of fun only making one main block and getting a whole quilt out of it! :)
Let’s start with the fabric requirements using the 2-tone option you see here. I bought 3 yards of each light and dark fabric and had enough for the binding and part of the pieced back.
Make the 36” Fierce Feathered Star as per the pattern directions.
Cut two 27” squares out of light fabric.
Fold the square in half diagonally as shown below, aligning all edges.
Use a long ruler to cut the large folded square in half, yielding 2 large half-square triangles.
Repeat with the other 27” square.
Very gently crease the bottom edge of a large triangle to find its center.
Find the midpoint of the Fierce Feathered Star block by folding it in half and marking its center.
Align the light triangle RST atop the FFS as shown below, matching the midpoints of each.
Carefully pin from the center outward. Be really careful not to pull or stretch the bias edge of the triangle.
Sew using 1/4” seam. Press (I like to press open).
Repeat with the other 3 triangles along the other 3 sides of the center block.
When all the setting triangles are sewn into place, the FFS will “float” in the center, meaning the center block does not extend all the way to the edge. As you can see in the photo below, there is a bit of a margin there.
Cut eight 2.75” x WOF strips of dark fabric.
Sew strips end-to-end (RST) in pairs to make four border strips. Press seams.
Trim two of the borders to 52”.
Tip: When I have to measure and cut pieces that are longer than my 36” cutting mat, I place a pin to mark the end of my mat (in this case 36”).
Then, I slide the pin to the 0” mark of my mat and do the math to figure out where I need to make the cut.
In this example 36” + 16” = 52”, so I make my cut at the 16” line of the mat.
To get nice, straight borders that don’t wave, ALWAYS measure & cut to the exact measurement first, pin and then sew to the quilt top.
Align border strip RST to one side of the quilt. At this point, the top is still square so it doesn’t matter which side you start with.
Pin each end of the border to the quilt top. Pin the center and continue pinning every few inches until the whole border is secured to the top.
Sew using 1/4” seam. Press.
Seam the 2nd border strip to the opposite side of the quilt top.
In the same manner as you attached the first two borders, cut the two remaining untrimmed border strips to 56.5” and sew to the other sides of the quilt.
The second border is only applied to two (opposite) sides to make the quilt rectangular. The top and bottom border are each made of fourteen half-square triangles (HST).
Cut four 10” squares of each the light and dark fabric to make a total of 32 HST using the Magic 8 method. Refer to page 11 of the Fierce Feathered Star pattern if you need a reminder.
Press and trim 28 (the remaining 4 won’t be used) of the HSTs to 4.5” square.
Arrange and seam together as shown. Attach to top and bottom of the quilt.
That’s it! “Quilt as desired” and bind… as they say in the biz. :)


It all started around 3000 BC with the Babylonians. They were one of the world’s first civilisations, and came up with some great ideas like agriculture, irrigation and writing. They plotted the paths of the Sun, the Moon and the planets, and recorded them on clay tablets (which you can still see in the British Museum). To the Babylonians we owe the modern ideas of angle, including the way that the circle is divided up into 360 degrees (owing to a small miscalculation, one per day). We also owe the Babylonians for the rather less pleasant invention of the (dreaded) taxman. And this was one of the reasons that the Babylonians needed to solve quadratic equations.
if is the length of the side of the field, is the amount of crop you can grow on a square field of sidelength 1, and is the amount of crop that you can grow, then
Quadratic equations and areas are linked together like brothers and sisters in the same family. However, at the moment we don’t have to solve anything – until the tax man arrives, that is! Cheerily he says to the farmer “I want you to give me crops to pay for the taxes on your farm.” The farmer now has a dilemma: how big a field does he need to grow that amount of crop? We can answer this question easily, in fact
Quadratic equations describe the motion of a baseball after it connects with a bat, and the acceleration of gravity at the Earth’s orbit.
A composite expression is similar in that it can be written as the product of two or more expressions. For example: x2 + 3x + 2 is composite because it can be written as (x + 1)(x + 2). (Recall that the FOIL Method shows that (x + 1)(x + 2) is equivalent to x2 + 3x + 2.) Here, (x + 1) and (x + 2) are factors of x2 + 3x + 2.
In general, a number is a factor of another number if the first number can divide the second without a remainder. Similarly, an expression is a factor of another expression if the first can divide the second without a remainder.
A prime number is a number greater than 1 which has only two positive factors: 1 and itself. For example, 11 is a prime number because its only positive factors are 1 and 11.
Factoring is a process by which a the factors of a composite number or a composite expression are determined, and the number or expression is written as a product of these factors. For example, the number 15 can be factored into: 1 * 15, 3 * 5, -1 * -15, or -3 * -5. The numbers -15, -5, -3, -1, 1, 3, 5, and 15 are all factors of 15 because they divide 15 without a remainder.
Factoring is an important process in algebra which is used to simplify expressions, simplify fractions, and solve equations. The next few lessons explain how to factor numbers, expressions, and equations.
A composite number is a number that can be written as the product of two positive integers other than 1 and the number itself. For example: 14 is a composite number because it can be written as 7 times 2. In this case, 7 and 2 are called factors of 14.
refresh on Solving Equations by Factoring
The Golden Arches ® Exposed!
On the blog dy/dan, there was a recent discussion about the shape of a bridge. One commenter joked about the Golden Arches of McDonald’s as being the most famous parabolas in America. As I am teaching quadratic modeling in College Algebra right now, I though I would find an equation for these parabolas. The problem is that the Golden Arches are not parabolas.
To find the equation, I scanned the Golden Arches from a placemat that I found at McDonald’s tonight. I took the scanned picture and imported it into GeoGebra. I picked five points on the outside of one arch, and five points inside of the arch. The picture is below.


|Statuss(Aktīvs)||Izdruka||Arhīvs(0)||Studiju plāns Vecais plāns||Kursu katalogs||Vēsture|
|Course title||Applied Mathematics|
|Total Hours in Course||200|
|Number of hours for lectures||24|
|Number of hours for seminars and practical classes||40|
|Number of hours for laboratory classes||16|
|Independent study hours||120|
|Date of course confirmation||21/03/2018|
|Responsible Unit||Department of Mathematics|
|Dr. paed., prof. Anda Zeidmane
Dr. math., asoc. prof. Svetlana Atslēga
Dr. math., asoc. prof. Natālija Sergejeva
Mg. math., lekt. Liene Strupule
|There is no prerequisite knowledge required for this course|
|The course is dedicated to acquire mathematical knowledge and skills necessary for the practical use of mathematical methods. The course deals with linear algebra, analytic geometry, limits of the function, derivatives of functions, integration, the complex numbers, 1st and 2nd order differential equations, number and power series and methods and applications of them. Introduce with Fourier series and double integral. Study course promotes mathematical thinking, practical transfer of knowledge to real tasks, problem solving by engineering students. During the course, students acquire skills in working with appropriate application software, such as “Matlab”.|
|Learning outcomes and their assessment|
|Upon successful completion of this course:
1.Students are able to manage and demonstrate knowledge and critical understanding of linear algebra, analytic geometry, limits of the function, derivatives of functions, integrals, complex numbers, 1st and 2nd order differential equations. Students manage the application of the acquired topics in practical examples related to the specialty of the Food Science. – 4 tests
2.Students are able to show understanding of the corresponding concept and regularities, to perform necessary caluculations and operations. Students are able to use appropriate software for calculations. – 40 practical and 12 laboratory works
3.Working in a group or doing work independently, student is able to apply the mathematical calculations corresponding to the specialty problem situation, to make a professional assessment and interpretation of the intermediate result of the calculations and the final results. – 12 independent works
|1. Determinants. Systems of linear equations and their solutions using Cramer’s rule and it’s application in Food extrusion process. (6h)
2. Matrices, operations with them and it’s application in preparation of food products recipes and production program. (5h)
3. Equation of a straight line in the plane. Basic problems of a straight line, their application in the study of linear processes. (5h)
Test 1. Elements of linear algebra and analytic geometry (1h)
4. Limit of the function, its properties. Indeterminate forms of limit and their solutions. Determination the point and type of discontinuity of function and it’s application in Thermal Processing in Food Industries (7h)
5. Differential calculations of one argument functions, their application in calculations of pasteurization and sterilization flow. Application of differential calculus in optimization of various processes. (10h)
6. Differential calculations of two argument functions, their application (4h)
Test 2. Limit of the function. Derivatives and its applications (1h)
7. Integrals. Calculation of indefinite integral by direct integration, method of substitution and integration by parts. (8h)
8. Calculations of the definite integral, their application in the calculation of area, volumes of revolution. Using calculations of integrals in extrusion processes. (8h)
Test 3. Calculations of integrals and their application
9. Complex numbers (1)
10. 1st order differential equations, their application (5h)
11. 2nd order differential equations, it’s using in structural and textural properties evaluation of food products. (5h)
Test 4. Calculation of differential equations, their application (1h)
12. Statistics: distribution rows of case size range, confidence intervals for mean values and variances, statistical hypotheses, testing of hypothesis, correlation and regression. Analysis and evaluation of statistical data working with appropriate application software. (12h)
|Requirements for awarding credit points|
|Description of the organization and tasks of students’ independent work|
|In writing form and by using the appropriate software, the following independent work must be completed:
Independent work 1. Linear Algebra
Independent work 2. Straight line in the plane
Independent work 3. Limits of the function
Independent work 4. Differential calculations of one argument functions
Independent work 5. Calculation of indefinite integral
Independent work 6. Calculations of definite integral, their application
Independent work 7. Calculation of 1st order differential equations
Independent work 8. Calculation of 2nd order differential equations
Independent work 9. Grouped frequency distribution
Independent work 10. Confidence intervals for mean values and variances
Independent work 11. Statistical hypotheses, testing of hypothesis
Independent work 12. Correlation and regression
|Criteria for Evaluating Learning Outcomes|
|The student can receive the accumulative exam if:
- all independent works are completed (all tasks are executed correctly);
- during the semester each test score is at least 4.
Failed tests can be repeated.
The student may overwrite unsuccessfully written test work during the study process, at times specified by the teaching staff. The student can rewrite the last test in the 1st week of the individual study and examination period at the time indicated by the lecturer.
The accumulative exam mark is the average mark of all tests. The written exam can be arranged at the time indicated by the lecturer, if all the independent works are defended (all tasks are performed correctly).
|1.Volodko I. Augstākā matemātika. I daļa. Rīga: Zvaigzne ABC, 2007. 294 lpp
2.Volodko I. Augstākā matemātika. II daļa. Rīga: Zvaigzne ABC, 2009. 392 lpp
3.Kronbergs E., Rivža P., Bože Dz. Augstākā matemātika. I daļa. Rīga: Zvaigzne, 1988. 534 lpp.
4.Kronbergs E., Rivža P., Bože Dz. Augstākā matemātika. II daļa. Rīga: Zvaigzne, 1988. 527 lpp.
5.Bula I., Buls J. Matemātiskā analīze ar ģeometrijas un algebras elementiem I daļa. Rīga: Zvaigzne ABC, 2003. 256 lpp.
6.Bula I., Buls J. Matemātiskā analīze ar ģeometrijas un algebras elementiem II daļa. Rīga: Zvaigzne ABC, 2004. 192 lpp.
|1.Cernajeva S., Vintere A. Mācību līdzeklis Augstākās matemātikas pamatu apguvei. Rīga-Jelgava, 2016. 198 lpp.
2.Šteiners K. Augstākā matemātika. I , II, III daļa. Rīga: Zvaigzne ABC, 1997. 96 lpp.; 1998. 116 lpp.; 1998. 192 lpp.
3.Zeidmane A. Didaktiskie materiāli augstākajā matemātikā. Pamatjēdzieni, pamatlikumi, pamatsakarības. Kopsavilkums. LLU, Jelgava. 2010. 39 lpp. e-materiāli
4.Lewin J. An Interactive Introduction to Mathematical Analisis. UK: Cambridge Umiversity press. 492 p.
5.Konev V. Linear algebra, Vector algebra and analytical geometry. Tomsk Polytechnic University, 2009. 114 p. file:///C:/Users/LIETOT~1/AppData/Local/Temp/Konev-Linear_Algebra_Vector_Algebra_and_Analytical_Geome-1.pdf 6.Uzdevumu krājums augstākajā matemātikā. Dz.Bože, L.Biezā, B.Siliņa, A.Strence. Rīga: Zvaigzne, 2001. 332 lpp.
|Compulsory course for Bachelor’s study programme “Food Quality and Innovations Bachelor”.|


Peter Urbani's Statistics - Co-Skewness worth 290bp
This month we look at the impact of different objective functions on the out-of-sample performance of optimised strategy allocations, and in particular of the important contribution of co-skewness to the overall skewness of the portfolio for those who care about higher moments
We show that the inclusion of higher moments to your portfolio construction process is worth +290 bp per annum over and above the performance of a broad Hedge Fund Index (Dow Jones Blue Chip Index). We also show that optimal weights for those who prefer higher odd moments (Mean, Skew etc.) are generally higher in the direction of those assets exhibiting positive relative skewness, or co-skewness, with either a benchmark or the portfolio itself. To illustrate, we conduct out-of-sample back testing on the 10 Main Dow Jones CSFB Blue Chip Hedge Fund Strategy Indices from Jan 2006 to Dec 2012. The initial look-back period is 24 months and rebalancing takes place bi-annually.
Objective functions used include; maximising the Sharpe ratio, which is equivalent to the classical minimum variance portfolio of MarkowitzĂ˘â‚¬â„˘s MPT, Maximising the ratio of the CAGR to both the normal, best fit and modified conditional value at risk (CVaR) or Expected Shortfall. This is sometimes called the STAR Ratio. As a control we compare the results to the benchmark index, and both a buy and hold and rebalanced equally weighted index.
The results show that the Modified and Best Fit methods outperform the Minimum Variance / Maximum Sharpe ratio method, the Benchmark Index and ......................
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King Calculator got accepted to the Google in education program and is being used in schools in the United States as an educational tool.
Your calculations and their result are automatically saved in and available using the history screen, you can view use previous expressions if you like.
- Fractions support.
- Percentage support.
- Memory variables.
- Ans button, that saves the last result for the next expression.
- Calculations history.
- Equations editor.
- Optional Casio style memory/percentage functionality.
- Trigonometric functions.
- Exponents, you can raise a number to any power.
- Squared root and cubed root (or any other root using the exponentiation button)
- Factorial and modulo operations.
- Logarithmic functions.
- Absolute value function and more.
- Ciel and floor.
- Plotting/Graphing functions.
King Calculator v2.0.8 Apk


Minimum Total Loss Rounding algorithms are quite useful for distribution problems if you need whole numbers after the distribution, as the final result of distribution.
Download Python script/module MinLossRounding_v1_Feb2019.py (version-1)
For example, you want to distribute a certain number of students to a number of available classrooms, approximately in proportion to the ground area (measured in square meter) of each classroom:
Distribute 180 students to 5 classrooms with given ground areas [25, 30, 20, 15, 35]
Sum of all given areas = 25 + 30 + 20 + 15 + 35 = 125 = sum([25, 30, 20, 15, 35])
If you distribute students to classrooms you will obtain following fractional numbers:
areas = [25, 30, 20, 15, 35]
d1 = [x*180.0/125.0 for x in areas] ([36.0, 43.2, 28.8, 21.6, 50.4])
Because there can’t be 43.2 or 28.8 students in a class, we need to round all these fractional numbers with minimum total loss, that is, with minimum total deviation from the original fractional number.
In my case, I defined rounding losses in proportionate terms. For example, proportionate round-down loss (deviation) for 43.2 is calculated by the function RoundDownLoss() as follows:
(43.2 - 43.0) / 43.2 = 0.2 / 43.2 = 0.004629629629629695
And round-up loss (deviation) by the function RoundUpLoss() as follows:
(44.0 - 43.2) / 43.2 = 0.8 / 43.2 = 0.01851851851851845
You can adjust the functions RoundDownLoss() and RoundUpLoss() if you have another concept of loss (deviation) in mind.


Janod Counting Caterpillars
Learn how to make up and compare numbers with Janod Counting Caterpillars game. This delightful wooden educational game will make the number concept easier to grasp by physically displaying the numbers and manipulating them in terms of volume.
Use the coloured beads to form the body of the caterpillars, to reproduce the numbers (shown as digit, fingers on hand or polygonal dots similar to dice) as per the game cards.
- Suitable for 3 years+
- Include wooden base, 33 cards, 20 green & blue beads, 2 caterpillar heads
- Learn the make of numbers, and later comparing if one number is larger/smaller than another


SciKnowTech Academics – Coursework for Grade 10 Real Numbers Euclid’s Division Lemma The Fundamental Theorem of Arithmetic Recap of Irrational Numbers & Revisiting Rational Numbers Polynomials Geometrical Meaning of the Zeroes of a Polynomial Relationship between Zeroes and Coefficients of a Polynomial Division Algorithm for Polynomials Pair of Linear Equations in Two Variables Methods of...
SciKnowTech Academics – Coursework for Grade 9 Number Systems Irrational Numbers Real Numbers and their Decimal Expansions Operations on Real Numbers Laws of Exponents for Real Numbers Polynomials Polynomials in One Variable Zeros of a Polynomial Remainder Theorem Factorisation of Polynomials Algebraic Identities Coordinate Geometry Cartesian System Plotting a Point in the Plane with given...
SciKnowTech Academics – Coursework for Grade 8 Rational Numbers Linear Equations in One Variable Understanding Quadrilaterals Practical Geometry Data Handling Squares and Square Roots Cubes and Cube Roots Comparing Quantities Algebraic Expressions and Identities Visualising Solid Shapes Mensuration Exponents and Powers Direct and Inverse Proportions Factorisation Introduction to Graphs
SciKnowTech Academics – Coursework for Grade 7 Integers Fractions and Decimals Data Handling Simple Equations Lines and Angles The Triangle and its Properties Congruence of Triangles Comparing Quantities Rational Numbers Practical Geometry Perimeter and Area Algebraic Expressions Exponents and Powers Symmetry Visualising Solid Shapes
SciKnowTech Academics – Coursework for Grade 6 Knowing our Numbers Whole Numbers Playing with Numbers Basic Geometrical Ideas Understanding Elementary Shapes Integers Fractions Decimals Data Handling Mensuration Algebra Ration & Proportion Symmetry Practical Geometry
SciKnowTech Academics – Coursework for Grade 5 Fraction Introduction Shapes and Angles Factors and Multiples Area and Perimeter Bar Charts Multiplication and Division Quantification Map Boxes and Sketches Patterns
SciKnowTech Academics – Coursework for Grade 4 Large Numbers Addition and Subtraction (4 & 5 digit numbers) Multiplication (3 digit numbers) Division the unitary method (2 & 4 digit numbers & 10,100,1000) Factors and Multiples (HCF & LCM) Geometry (measurement, comparison of angles, types, closed figure, quadrilateral & circles) Metric Measures Fractions Decimal System Money...
SciKnowTech Academics – Coursework for Grade 3 Fun with Numbers (introduction to numbers, types of numbers, etc.) Large Numbers (4 digit numbers, addition & subtraction) Geometry and Patterns Multiplication Division Fraction Money Time Measurements Data Handling
SciKnowTech Academics – Coursework for Grade 2 Numbers (2 digits and 3 digits) Addition (2 & 3 digits) Subtraction (2 & 3 digits) Multiplication (tables 1 to 10) Division Shapes and Patterns Time (calendar; days & months) Money Measurements Data Handling Concept of Fractions


Transportation. Includes Driving, Traffic, Parking, Cycling, Road construction, maintenance and planning.For more examples of hand odds, see our Poker Hands Odds page.Find out more about seven of the most common graphs in statistics. 7 Statistics Graphs. Search the. Another common way to represent data graphically is a pie chart.
Lady Gaga Music Career Statistics Data Lady Gaga total net worth $250,000,000 Number of Grammy Awards won 5 Number of MTV music. Poker Face: 9,800,000: Hair.
Basic Poker Math & StatisticsThe 20 Hold'em Poker odds & statistics you should know if you want to improve your game. Each one is remarkably simple but effective - learn more here.The first chart shows the total amount of online poker players on the networks we have been able to gather statistics from. The numbers are peaking player numbers and.Easy to use Texas holdem odds chart for every important situation. This site is dedicated to making you a better player.
We will be adding some live-scenario illustrations on this page soonn as well.
The 6 Best Poker Starting Hands You Must Know About
Pre-Flop Poker Probability Statistics - Chances Dealt AA AcesCalculating Poker Odds for Dummies. Poker Pot Odds & Starting Hands Chart. Here's our at-a-glance guide to pot odds in poker and which hands to play.This is a discussion on Excellent spreadsheet for tracking your poker results within the online poker forums,. 6-max Pre flop chart.Discover and follow Loc Truong on the poker social network: United States and international ranking, results, tournaments, blog, pictures and endorsements.There are 20 Hold'em statistics you should know if you want to improve your game. Each one is remarkably simple but effective - learn more here.Poker percentage odds chart. Use this chart for working out the percentage odds of completing a draw based on your number of outs.
Complete ranking of poker hands for texas. Poker Hand Rankings - Texas Holdem Starting Hands Chart. The statistics are based on 115,591,080 pair of pocket.How to calculate the odds in Open Face Chinese Poker? OFC Odds, 3-handed Open Face Odds, Open Face Chinese Odds Charts, Open Face Chinese Three handed Chart, Open.Practical Poker Math: Basic Odds & Probabilities for Hold'em & Omaha [Pat Dittmar] on Amazon.com. *FREE* shipping on qualifying offers. What are the odds of winning.
Free Poker Statistics Odds Calculator, Tracker & Strategy
Basic Poker Odds. by FlopTurnRiver | Jan 1, 2010. Expected Value Hand Charts – Statistics. For our complete list of poker charts, visit our Poker Odds Chart page.Texas Hold'em Rules. A single 52-card deck is used. All cards count as its poker value. Aces may be high or low. One player is designated as the dealer, usually with.
Poker Pro Labs - Top Shark Pro - Poker Rankings and
Video Poker Statistics - Poker Strategy
Take a look at the official homepage - Foot Locker UK Home
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Poker Odds Calculator is a free Texas Hold'em and Omaha Poker odds calculator.POKER MATH MADE EASY. Below is the chart that I use to calculate all the odds at the poker table. At first, this chart looks pretty intimidating.Hold'em Hole Card Pocket Rank Statistics Chart. Compare starting hands versus other hole cards.
About the Lines of Code Metric - Atlassian Documentation
Follow these hand charts and learn how to play your starting hands at Texas Holdem.
Monopoly Board Location Probabilities (Statistics, Frequency)
Free online texas hold'em poker odds calculator. Calculate probabilities, outs and odds for up to 12 players. Get statistics for any starting hand and flop, turn and.Texas Hold 'Em is the most popular version of poker worldwide, it can be a fun family card game or a competitive game with high stakes.These charts are available for free from our DOWNLOADS PAGE.The software provides a table overlay so you can see the numbers on your poker table as you play.Chance Luck & Statistics by Horace Levinson. and with specific applications to poker, roulette, lotteries, dice games, bridge, and other games involving chance.
Lady Gaga Album Sale Statistics – Statistic BrainRyan Fee's Statistics. AKA Ryan Fee. The Largest Live Poker Database. Players: 530,938. Help to improve The Hendon Mob Poker Database by donating. Ryan Fee.
Poker Sharpener helps you make more money by providing real time statistics, and giving you the tools to analyze your game and become a better poker player. See stats and player profiles right on the poker screen. Click on any player to see details of how they play.Dead Money's guide to hold'em poker strategy, Lesson 14: Basic Poker Math & Statistics.I've put together a collection of poker spreadsheets that are already in the public domain. If you need: * A starting hands chart for no limit/limit *.Statistics 120 Good and Bad Graphs. sometimes because they don’t understand statistics.


What is Correlation
Correlation includes any broad category of statistical relationships having dependence. Similar instances of the phenomena of dependence consist of the correlation between the physical features of the offspring and their parents, and the correlation between price and demand of any product.
Uses of Correlation
Correlations have usefulness in terms of recognizing a predictive relation which can be extracted in practice. For instance, any electrical item can yield less power on a mild day on the basis of the correlation between weather and the demand of electricity. There is a causal relation in this example as the extreme weather results in more usage of electric power by the people for cooling and heating purposes, but statistical dependence is not enough to show the occurrence of this type of causal relation.
Basically, dependence relates to any circumstance where random variables are unable to satisfy a mathematical situation having probabilistic independence. Generally, correlation means any departure of more than two or two random variables from independence, however in technical terms it implies any of the various specialized kinds of relations among mean values. A number of correlation coefficients exits, sometimes denoted by r or p, calculating the level of correlation. The very common ones include Pearson Correlation Coefficient, that is only sensitive to a linear relation between two variables. There are more robust correlation coefficients other than this which means that they are more sensitive to nonlinear relations. In order to calculate dependence between two variables mutual information can be applied too.
What is Correlation Matrix
A correlation matrix has the purpose of finding out the dependence among various variables on the same time. The results contain a table having correlation coefficients among every variable and the rest of them. There are various techniques for correlation analysis. These include Kendall and Spearman correlation analysis based on ranks and Pearson Parametric Correlation. A correlogram is used for visualization of correlation matrix.
While talking about a correlation matrix, one usually implies a matrix having correlations like Pearson’s. But, such correlations are impacted by outliers, non normality, unequal variances and nonlinearties. Pearson correlation coefficients’ main competitors include the Spearman-rank correlation coefficient. The latter correlation is measured using the formulas of Pearson correlation to the data ranks instead of real data values. This is done because a number of distortions which impact the Pearson correlation are lessened. For permitting you in comparing the two kinds of correlation matrices, there can be a display of a matrix of differences. This permits you in finding out which variable pairs need more investigation. For this purpose, you can specify a group of partial variables. Linear impact of such variables is lessened by moving them out from the matrix. This gives a statistical adjustment to the rest of the variables making use of various regressions. It should be noted however that in Spearman correlations case, the moving of variables takes place when the complete correlation matrix is established.
In the cases having above one independent variable, a group of all correlations pair-wise are briefly shown in the form of a correlation. The purpose of studying these in correlations in regression analysis has two purposes: firstly it is to locate the outliers and to find collinearity. When it comes to outliers, there must be significant distinction among the Pearson correlation coefficient, parametric measure as well as the nonparametric measure and Spearman rank correlation coefficient. In collinearity’s case, the correlations being high pair-wise can be the initial pointers of problems of collinearity. There is an undue influence on the Pearson correlation by outliers, non-linearities, unequal variances and non-normality. As a consequence of such problems, the better option in studying the relation among variables is the Spearman correlation coefficient that has its basis upon the ranks of data instead of the real data. Eventually patterns of missingness in various correlation and regression analysis could be extremely complicated. As a consequence, missing values could be omitted in a row-wise or pair-wise manner. In the cases having fewer observations with missing values, it may be preferred to make use of row-wise omissions, particularly with large data sets. The row-wise procedure of omission deletes the whole observation from analysis. Whereas, if the pattern of missingness is scattered randomly in the whole data and the utilization of row-wise omission would delete more than 25% of observation, the process of pair-wise omission for missing values will be a better option to gain the essence of relation among variables.
Where this technique is said to use the entire data, the correlation matrix that results from this might have interpretation and mathematical issues. This correlation matrix mathematically might not possess positive determinant. As every correlation might have its basis on various row sets, practical analysis can be a problem if it is not logical.
The monotonic link among variables in terms of ranks is measured by the Spearman correlation coefficient. It calculates if one variable rises or lessens in amount with another even if the relation between the two is not bivariate normal or linear. Technically, both these variables are given ranks separately, and the computation of ordinary Pearson correlation coefficient is done on ranks. Such non-parametric correlation coefficient has a better measurement in terms of relation between two variables in cases where non-constant variance, outliers, non-linearity, and non-normality might be present between the under investigation two variables.
Reading a Correlation Matrix
The calculation of correlation matrix is done by the data variables’ sample variance. For instance, if you have to calculate correlation coefficient of x and y, two variables, the following formula will be applicable:
This formula is applicable to all variables which form the matrix of variance-covariance for making a correlation matrix. But, in the first row first element, second row second element and third row third element of correlation matrix will always be one. This is so due to the fact it demonstrates correspondence of a variable with itself. Whenever you have to calculate the correlation coefficient for x variable with itself, you will always get one.
It can also be observed that the correlation matrix is symmetric too. This is because the upper part of the matrix is symmetric to the lower part of it.
You can see that the correlation matrix is a symmetric matrix as well. The upper half of the matrix is mirrored by the lower half of the matrix. From the above example it can be observed that all the values of correlation coefficients can be seen between plus and minus 1. It is not possible for the coefficient to be an exact minus 1 or plus 1. This implies that in reality, there will be no variable that has a stable relation with some other variable at all times. If there is a coefficient which is positive, an increase in the value of one variable would demonstrate a corresponding increase in the other variable’s value.
If the value of a coefficient is close to 1, there will be a closer relation between the two data variables. Also, if the coefficient’s value is negative or positive but is very less, it implies that there might be less or no relation between the data variables. In reality, an example of like this could be taken: the relation between gold prices and medicine prices-an increase or decrease in the price of gold will have little or no effect on the price of medicine, which means that there is no or little relation between these two variables.
Correlation in the Real World
Correlation Matrix in Stock Market
In the stock market, a correlation matrix might show the long-term, short-term or medium-term relation among data variables. For instance, if the prices of silver and gold are considered, it can be observed that in the long-time, the prices of both are dependent on each other: when one rises the other rises too. This demonstrates a positive correlation between them in long-term. But, this might not be the situation in medium-term or short-term for both of them. It can be seen hence that a correlation matrix can be of great use to the traders. For making an accurate prediction, data is mostly gathered from a considerably long time span, put in a numerical form and then examined by a correlation matrix.
Correlation Matrix Used by Actuaries
Correlation Matrix is also made use in actuaries for the purpose of measuring risk for banks and big organizations. The data variables in this case are risk factors and an examination is done of their relationship. This might be categorized as high risk which is of above a value of 0.75, low risk which is less than 0.25 and medium risk that is between 0.25 and 0.75. Usually, it is not possible to measure a correlation matrix when there are several risk factors included. In various situations, matrices become very difficult to understand. To find a solution to this problem an eigen decomposition matrix is calculated from standard matrix that makes it a lot simpler to understand and study.


You are using MADlib for Linear Regression analysis. Which value does the statement return?
SELECT (linregr(depvar, indepvar)).r2 FROM zeta1;
A. Goodness of fit
C. Standard error
Which data asset is an example of quasi-structured data?
A. Webserver log
B. XML data file
C. Database table
D. News article
What would be considered "Big Data"?
A. An OLAP Cube containing customer demographic information about 100, 000, 000
B. Daily Log files from a web server that receives 100, 000 hits per minute
C. Aggregated statistical data stored in a relational database table
D. Spreadsheets containing monthly sales data for a Global 100 corporation
A data scientist plans to classify the sentiment polarity of 10, 000 product reviews collected from
the Internet. What is the most appropriate model to use? Suppose labeled training data is
A. Na?ve Bayesian classifier
B. Linear regression
C. Logistic regression
D. K-means clustering
In which lifecycle stage are test and training data sets created?


I would be very grateful if the developer could change the win rate calculation in the performance report.
Win rate is currently being calculated using number of winning trades vs number of losing trades. This does not work correctly when trading multiple contracts because of the exchange matching system.
For example, one long with 10 contracts could be matched with 3 short sellers (5 shorts, 3 shorts, 2 shorts).
In the report performance this 10 contract long would be recorded as 3 trades. However this is 1 trade. For this reason, the win rate is calculated incorrectly.
For the win rate to be calculated correctly, the formula needs to use number of winning vs number of losing contracts and NOT number of winning vs number of losing trades.
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A Target Variable: The name of the new variable that will be created during the computation. If you are analysing your data using multiple regression and any of your independent variables were measured on a nominal or ordinal scale, you need to know how to create dummy variables and interpret their results. Descriptive Statistics Mean Std. I.e. The SPSS INDEX function returns the position of the first occurrence of a given expression within a string.If the expression does not occur in the string, it returns a zero. Variables can be combined in SPSS by adding or multiplying them together. In the original data, a variable appears in a single column. When you have created the dataset by typing your data into SPSS, and after you have tested for the internal consistency of the scale (use Cronbach’s α), it’s time to create a new variable. I want to do this, as I want to be able to run tests on the mean temperature in Tampa over days 0-20, relative to days 0-20 in other cities. SPSS (The Statistical Package for the Social Sciences) software has been developed by IBM and it is widely used to analyse data and make predictions based on specific collections of data. SPSS Statistics SPSS Statistics procedure for version 24 and earlier. The "-3"in the code I showed you adjusts the additive scale with a range of 4 to 20 to 1 to 17. ONE WAY TO DO AN INDEX WITH SPSS. In the original data, a variable appears in a single column. This can easily be achieved with the "rename variable" command. The most common approach is the factorial design, in which each level of one independent variable is combined with each level of the others to create all possible conditions. The nine steps that follow show you how to create a clustered bar chart in SPSS Statistics version 24 and earlier using the example on the previous page. Viewed 639 times 1. 1) From the Data menu, select Restructure… 2) Then select “Restructure selected cases into variables”. He creates a summary index of his outcome variables. Using SPSS Reference Variables and an Index to Create a New Variable. In SPSS Statistics, we created three variables: (1) HDL, which is the HDL cholesterol concentration; (2) physical_activity, which is the participant's level of physical activity measured in the number of minutes of exercise performed per week; (3) body_composition, which is the participant's body composition (i.e., normal weight or obese). I want to turn the seven variables into one variable, with 1=Native American, 2=Asian, 3=African American, and so on. Break Variable(s) are cases which are grouped together based on the values of the break variables. SPSS: Frequency table of multiple variables with same values Below are the steps to generate a frequency table of multiple variables that have the same values. There are scores on Maths, English, Biology and Chemistry from 13 students. many SPSS graphs can only be generated after stacking the relevant variables on top A little known feature of SPSS' INDEX function is an optional third argument known as the divisor. In statistics and research design, an index is a composite statistic – a measure of changes in a representative group of individual data points, or in other words, a compound measure that aggregates multiple indicators. Subject: Factor analysis, Regression 8 April 2015. Both SPSS and R run their advanced data visualizations using GPL. Click Add. To create one, you must select possible items, examine their empirical relationships, score the index, and validate it. See the syntax "Number consecutively cases with the same id.sps". Remember that there’s an important difference between a variable label and a value label. Hi, I am new on SPSS, I hope you can provide some insights on the following. GGRAPH GPL Language to create a graph with multiple variables using the same category Good Evening more advanced users of SPSS and R! Each unique combination of break variable values defines a group. OLS Equation for SPSS • Multiple regression Model 1 BMI 0 1 calorie 2 exercise 4 income 5 education Yxx xx β ββ ββ ε =+ + ++ + Using SPSS for Multiple Regression. I showed one way of creating and additive index that accounts for the expanded range. Since Forsyth claimed that this instrument measures two constructs, we shall ask SPSS to create only two factors. For example, I am constructing a variable named Maternal Hardship that is an index/average of the mother's response to 14 different questions where possible answers are yes/no, thus binary. I can't figure out how to use the aggregate function to create new variables to avoid losing these days. We view these as preliminary steps that lead to the construction of indices from household level variables, for instance to create indicators of poverty, e.g., Sahn and Stifel (2000). Move parasp from the list on the left into the Numeric Expression box using the arrow button, input a ‘+’sign using the keypad, and then add pupasp. RENAME VARIABLE (varx = vara). The restructured data will contain one new variable for each unique value in these columns. We use the Compute function to create totally new variables. What if I do not have any data in my data file but I would still like to create an ID variable with values between 1 and 10. • Third, adjusted R2 need to be compared to determine if the new independent variables improve the model. For example, a very common situation is a researcher needs to average the values of the 5 variables … The restructured data will contain one … In this article we look at how to stack data that has been loaded into SPSS Statistics, using both the interactive wizard and using syntax via the VARTOCASES command. To create a new variable in SPSS, use the compute command. Click OK . of variables involved. Also covered is the difference between row numbers (which are a part of the spreadsheet) and ID variables (which are a part of the dataset and act as case identifiers). This provides estimates for both models and a significance test of the difference between the R-squared values. To begin with, get into SPSS and click on the “analyze” drop-down menu: Leave the cursor on the “scale” choice and the two choices at the right will appear and you click on “reliability analysis.” Then, you’ll see another window like this: Also note that in the output, SPSS tells us which variable were used to create the new variables, how many cases were in the long data set (called "Cases In" in the Processing Statistics table), how many cases are in the wide data set (called "Cases Out"), and how many index values were created. I have a data base of patients which contain multiple variables as yes=1, no=0. To … the number of categories – 1) and include these new dummy variables in your regression model 3. SPSS has a nice little feature for adding and averaging variables with missing data that many people don’t know about. If the expression does not occur in the string, it returns a zero. SPSS INDEX Function By Ruben Geert van den Berg under String Variables. Index variables are variables in the current data that the wizard should use to create the new columns. Essentially, I have a log which contains a Unique identifier for a subject which is tracked through multiple cases. Data stacking is a data preparation step where a data set is split into subsets, and the subsets are merged by case (or stacked on top of one another). I have one row per subject, but each subject has done multiple different conditions as well as procedures. To create a new variable in SPSS, use the compute command. EXECUTE. Basically, any observation with values of 1 on all four variables is assigned a score of 1; observations with values of 5 on all four variables receive scores of 17. From the top menu bar in SPSS, select Transform -> Compute variable. The divisor divides the search expression into substrings of length n. The position of the first occurrence of one of these substrings is returned. Next, we'll substitute that into a SUBSTR function in step 4. Section II provides a general overview of multivariate techniques as the collective study of a group of outcome variables. If you switch to the Variable View on the main screen you will see that bothasp has appeared at the bottom. This tutorial covers how to create a new dataset in SPSS by manually entering data. You should now see the following dialogue box. In this example we consider data from a simple survey which asked people about how they rate different technology brands. Move the variables that should be used to form the new variable groups to the Index … Ask Question Asked 3 years, 3 months ago. You can use most basic mathematical expressions to combine variables into new variables with compute statements As explained in the "Get File" and "Save File" chapters, existing variables can be renamed either when retrieving or saving data. 1 Introduction Recoding may be needed in a number of diﬀerent situtions: • To categorise a continuous variable. Select a Set Name and (optionally) a Set Label. For this example let’s create a new variable which combines the two existing questions in the LSYPE dataset: 1) Whether or not the parent wants their child to go to full-time education after the age of 16 (the variable named parasp in SPSS, 0 = no; 1= yes). Easy Excel Template for Renaming & Relabeling Multiple Variables in SPSS July 24, 2017 // by Dana Wanzer // 2 Comments Unfortunately, Qualtrics does not do so well in renaming variables on the site, so I typically just leave the defaults and recode later in SPSS. SPSS will also create the interaction term; simply list the two variables … Researchers often want to combine two or more variables in order to create a new variable. When deciding what type of graph to produce, you first need to think about (1) the type of data you have collected: interval, ordinal or nominal data. The array, meas, has four columns, so the dataset array, ds, has four variables.The default variable names are the array name, meas, with column numbers appended. You estimate a multiple regression model in SPSS by selecting from the menu: The number of variables in the data decreases, and the number of cases increases. Simply type a name for the new variable in the text field. The variables can be character or numeric or mixed (one character and the other one is … Because prog is a categorical variable (it has three levels), we need to create dummy codes for it. play in index construction and in initial stages of data exploration with specific subsets of the survey data, before further analysis is done to address specific survey objectives. It combines the use of the divisor with LOOP, SUBSTR and CONCAT in order to do so. To initiate our index construction, we need to create the new variable so that SPSS will know where to put the results of our work. Before you start stacking you should work out: 1. You can use this command in many ways: To create a variable called total equal to the sum of variables v1, v2, v3, and v4, the syntax is: compute total = v1+v2+v3+v4. Now click Extraction. At … Hello everybody! When creating a new, aggregated data file, all break variables are saved in the new file with their existing names and dictionary information. Therefore, [email protected] is zero for this case. This short video details how to convert an nominal or ordinal variable that have more than two levels associated with them into a set of dichotomous Dummy Variables… This makes step 4 come up with an incorrect domain, hence the correction at the end.A better option here is to use a single IF command that computes the domain only if @ is present in the email address. SPSS handout 3: Grouping and Recoding Variables Richard Buxton and Rosie Cornish. How do I create a scale in SPSS? ... but you are interested in the latent construct that is indicated by a number of variables. You can use most basic mathematical expressions to combine variables into new variables with compute statements The syntax below demonstrates how to do so. Using SPSS Reference Variables and an Index to Create a New Variable. SPSS Output Tables. The easiest method to find the list of all system variables is to open SPSS Help and search for "$casenum". Creating dummy variables in SPSS Statistics Introduction. There are many kinds of conditions you can specify by selecting a variable (or multiple variables) from the left column, moving them to the center text field, and using the blue buttons to specify values (e.g., “1”) and operations (e.g., +, *, /). You can use this information to ensure that the reshaping went as desired. Here is an example: variable label Fake_Var1 "My Fake Variable" Fake_Var2 "My Second Fake Variable". In this case you will want to create a scale variable, constructed from your items. Written and illustrated tutorials for the statistical software SPSS. Using SPSS, the data can be restructured from long format into wide format. We'll first find the position of the first (and only)@ in step 2. I would like to create a new variable (an ID variable) which would number each case in my data, starting with 1 and ending with n, the number of cases in the file. There are three common forms of descriptive statistics: 1. For example, you may have measured people’s BMI (body mass index) as a continuous variable but may want to use it to create groups Here we present the steps for doing this using the above example data. Indexes – also known as composite indicators – summarize and rank specific observations. Say we have data holding some email addresses and we'd like to see which domains are used most. Merging the variables. As a rule of thumb, always use it as CHAR.INDEX. In the new data file, that variable will appear in multiple new columns. I would like to create a new variable (an ID variable) which would number each case in my data, starting with 1 and ending with n, the number of cases in the file. Researchers often want to combine two or more variables in order to create a new variable. I am using a public database named Fragile Families and child wellbeing study and I have to construct several variables that are indexes. Item Selection The first step in creating an index is selecting the items you wish to include in the index to measure the variable of interest. - Using syntax: COMPUTE id=$CASENUM. Factor scores are essentially a weighted sum of the items. The SPSS INDEX function returns the position of the first occurrence of a given expression within a string.If the expression does not occur in the string, it returns a zero. variables that are strongly associated with the dependent variable, Pearson r test could be used for interval-ratio variables with the dependent variable). Index, and how many are allowed to be missing which Asked people about how they different. Structures by using the above example data that into a new variable in SPSS by selecting from the data,... Weighted sum of the first occurrence of a group you switch to the factor scores needed a... Data that the wizard should use to create 2 dummy variables in the original data, a variable appears a... Of cases increases constructs, we shall ask SPSS to create a variable! Of variables a summary index of his outcome variables for each email does. One variable, '0123456789',1 ) the divisor divides the search expression into substrings of length 1, rendering digits... Box Plots in SPSS by adding or multiplying them together an SPSS data file, that variable appear. Descriptive statistics for the statistical software SPSS am using a single column of thumb, always use it CHAR.INDEX! Factor and scoot all 20 variables ( how to create an index from multiple variables spss through Q20 ) into variables! Variable can be combined in SPSS by adding or multiplying them together covers how to create,... Need to create the new columns of patients which contain multiple variables as,... April 2015 i have to construct several variables that are indexes `` variable. 3=African American, 2=Asian, 3=African American, 2=Asian, 3=African American, 2=Asian, 3=African American,,. Option and specify a Counted value of 1 and earlier outcome variables an important difference between the R-squared.... That you give to individual fields ( like responses ) in an SPSS data file SPSS handout:. 07 Dec 2014, 09:16 their experiments contain multiple variables as yes=1, no=0 survey which Asked people how. Base of patients which contain multiple variables are the names that you give individual... Happens, select Transform > run PENDING Transform ) select Restructure… 2 ) then “... The collective study of several key variables, which i am trying to reduce 2 dummy variables in to. Used the following code, suggested previously through the great community here, to create a new, grouping in! “ Restructure selected cases into variables ” combine variables into one variable score the index, and how stacked! A name for the expanded range adjusted R2 need to be missing survey... Is tracked through multiple cases variables in the tool bar at the bottom, constructed from your items that instrument... Concat in order to create totally new variables with the `` Transform '' - `` variable! The filename identifies the variable as a multiple-response set how do i Go using. Substitute that into a SUBSTR function in step 2 Double-click the name of first! Up data step 1 Go to `` file '' in the string, it returns a zero you switch the! R2 need to be stacked, and validate it learn how to create new... Common forms of descriptive statistics: 1 dataset is to calculate an index select possible items, examine empirical. Deviation, and then click `` Open. change a variable you wish to multiple by a constant of?! System variables is to Open SPSS Help and search for `` $ casenum '' name. The function group list essentially a weighted sum of the page in SPSS having... Type ABORT ( if nothing happens, select Restructure… 2 ) then select “ Restructure selected cases into variables.... Shall ask SPSS to create a new variable contain any @ addresses and we 'd to... However, you must select possible items, examine their empirical relationships, score the index, ID or variable. While specifying how many are allowed to be compared to determine if the expression does not occur in image... Pending Transform ) ’ s an important difference between a variable name in present! A constant of 2 's called composite index when we create an index for two or more in. Derived from its factor loading everything after the @ sign left corner of first... Then click `` Open. one way of creating and additive index that accounts for the expanded range sign... In composite index from binary variables 07 Dec 2014, 09:16 i have one row per subject but! Within the dataset is an optional third argument known as Indicator variables... then you will need to create new! Step 2 Double-click the name of the first ( and only ) @ in step 4 data of. And Chemistry from 13 students, '0123456789',1 ) the divisor is 1 we 'll first find the list of system... The text field depends on how strongly it relates to the factor depends... Illustrated tutorials for the variables within the dataset the Groundwork: survey are! Both SPSS and r run their advanced data visualizations using GPL single number.Examples include mean... The “ Target variable ” window, click Analyze, data Reduction, and... In these columns went as desired, condition_2 etc file you wish to Open SPSS Help and search ``. A weighted sum of the difference between a variable appears in a number of categories 1. On how strongly it relates to the variable View on the main screen you will want turn! R test could be used for search specific values: variable label Fake_Var1 `` Second... Test of the first ( and only ) @ in step 2 how! Either numeric or string entering data like responses ) in an SPSS data file of... `` RENAME variable '' command @ in step 4: Compute var2 = var1 * 2 in the Compute. Name of the items, called the factor scores, English, Biology Chemistry... Models and a significance test of the items, called the factor third, R2! Second Fake variable '' reshaping went as desired wizard should use to create multiple box how to create an index from multiple variables spss in SPSS the group. A multiple-response set and only ) @ in step 4 dummy variables also known as the divisor is 1 there! Using SPSS Reference variables and an index for two or more variables in the current data the... Search for `` $ casenum '' up after approval from a moderator substrings of length the! Could be used for interval-ratio variables with the dependent variable, constructed from your items optional third known. Relationships, score the index how to create an index from multiple variables spss and then click `` Open. system variables is to calculate index! • to categorise a continuous variable PENDING Transform ) the steps for doing this using the RENAME! ] is zero for this case you will see that bothasp has appeared at bottom! Regression 8 April 2015 variable Coding area, select Transform > run PENDING Transform ) create a new that. Reshaping went as desired of length 1, rendering the digits 0 through 9 variable window... Buxton and Rosie Cornish the use of the divisor 's an error in the “ variable. Figure out wellbeing study and i have to construct several variables that are indexes,. Variable name in your regression model in SPSS by adding or multiplying together! Holding some email addresses and we 'd like to see which domains are most... Berg under string variables unique identifier for a subject which is tracked through multiple cases R-squared. Involve the simultaneous study of a group of outcome variables to ensure the! Bar in SPSS nothing happens, select the Dichotomies option and specify Counted! Involve the simultaneous study of several key variables Compute var2 = var1 * 2 working file variable '' command,. Summary statistics – Numbers that summarize a variable appears in a single column command in SPSS by adding or them. Three common forms of descriptive statistics for the statistical software SPSS in their.. While specifying how many stacked variables will there be in the data since the last email address does n't any... Then: Compute var2 = var1 * 2 to … you can also create multiple side-by-side box Plots SPSS having! The “ Target variable ” window, click in the data which belongs together is spread within columns! From the menu: Hello everybody can easily be achieved with the dependent variable, Pearson test. The variables within the dataset, score the index, values of multiple variables to... Up data step 1 Go to `` file '' in the current that... Their empirical relationships, score the index, and validate it Groundwork: survey variables are the names that give... The collective study of several key variables argument known as the collective of..., there ar… RENAME variables, no=0 third argument known as composite indicators – summarize and rank specific.! Involve the simultaneous study of a group and child wellbeing study and i have construct. Be compared to determine if the expression does not occur in the latent that. Variables are variables in the variable View on the main screen you will see that bothasp has at! The search expression into substrings of length n. the position of the between... Consider data from a simple survey which Asked people about how they rate different technology.... New variable in SPSS, use the Compute command up data step Go! A moderator, values of multiple variables as yes=1, no=0 step.!, grouping variable in SPSS grouping and Recoding variables Richard Buxton and Rosie.. One of these substrings is returned as CHAR.INDEX wish to change a variable name in your regression in. The list of all system variables is to calculate descriptive statistics for the statistical software SPSS label Fake_Var1 `` Fake! Third, adjusted R2 need to create totally new variables with Compute statements to! Should work out: 1 up data step 1 Go to `` file in! Does not occur in the filename identifies the variable as a multiple-response set has done multiple different as!
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Stock screening results for the parameters you selected (or pre-selected parameters) are shown in the table below.
All our stock screeners are supplemented with backtesting on historical data, that also includes a scatter plot of past performance of stocks that meet you screening criteria. This is a very powerful combination. Not only you get the summary results (the mean and the median), but you also have a graphical representation of performance of each stock in each past year.
Please remember that past performance may not be indicative of future results. Please also note the significant distribution of the results and that the “median” stock underperforms the average by a very large margin. That means that the average is propped up by a relatively small number of stocks that perform spectacularly. Make sure you do not sell them prematurely.
Contrary to common belief, Benjamin Graham and David Dodd did not provide any indication that they used a formula or a specific algorithm for determining intrinsic value of a common stock. According to them, "security analysis does not seek to determine exactly what is the intrinsic value of a given security". It can only asses if the price is low or high enough. The intrinsic value is a range with vaguely defined limits, not a specific number.
In The Intelligent Investor, Benjamin Graham provides a simple formula, that, in his own words, only "approximates the results of the more elaborate calculations in vogue" (i.e. other methods) for the valuation of growth stocks. He never actually suggested or implied that that the formula gives the "true value" of a growth stock. This formula appeared in the text in the context of the discussion how unreliable predictions of future growth rates are.
The formula was slightly revised in 1974 to adjust for variations in market interest rates and was described as follows:
where V* is intrinsic value of a stock, EPS is the company’s last 12-month earnings per share, 8.5 is the constant representing the appropriate P/E ratio for a no-growth company as proposed by Graham, g is the company’s long-term (five years) earnings growth estimate, 4.4 is the average yield of high-grade corporate bonds in 1962, when this model was first introduced, and Y is the current yield on 20yr AAA corporate bonds.
Despite specific warnings from the author, the equation, known as the Benjamin Graham formula, is commonly used today for valuation of stocks.
Overzealous Graham followers even introduced the notion of relative Graham value (RGV), which is calculated as the ratio of stock's intrinsic value (V*) to its current price (P):
For overvalued stocks RGV is less than one, while for undervalued ones it is greater than one.


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Put in your home loan details to get an instant estimate of your home loan repayments and interest charged. Loan must not be less than $40,000. Please adjust the deposit. Investment loans have a maximum 90% LVR.


12:00am - 11:59pm
Registration Deadline: January 3, 2020
Dates: January 13 to April 5, 2020
Venue: Fully online courses
Offered by: University of Victoria, Continuing Studies and Population Data BC
Website Link: https://www.popdata.bc.ca/etu/PHDA/courses/02
This is a basic course in epidemiology which also covers a variety of analytic topics not commonly addressed in elementary statistics courses. This course will introduce students to the field of epidemiology. Students will critically evaluate articles in the epidemiologic literature and examine epidemiologic methods including:
- data collection
- study design and statistical analysis
- relative risk
- contingency tables
- logistic and Poisson
- measurement error and exposure misclassification
- imputation of missing values
- multilevel regression models in epidemiology
- Explain basic concepts in descriptive epidemiology such as incidence, prevalence, mortality, morbidity and effect.
- Distinguish among common epidemiological designs such as case-control, cohort, cross-sectional and randomized controlled studies.
- Identify major categories of bias that can affect the validity of epidemiological studies.
- Apply common measures of association such as relative risk, odds and odds ratios, attributable risk, attributable risk percentage and population attributable risk to epidemiological data.
- Employ common tools of epidemiological statistics such as logistic and Poisson regression and become oriented to multilevel regression models to analyze appropriate data.
Admission to the Professional Specialization Certificate in Population Health Data Analysis or permission of the Faculty Advisor.
Working knowledge of how to interpret P values, null hypothesis and confidence intervals and some experience with SAS, Excel, linear regression models and natural logarithms including exponentiation using a calculator or the “exp” function in Excel.
A solid grasp of high school math skills, including the ability to use logarithms capably and to work competently with percentages and ratios.
Instructor: Allison Scott
Allison Scott is a Research Scientist with the Child and Youth Data Laboratory (CYDL). She completed her PhD in the Department of Epidemiology, Biostatistics and Occupational Health at McGill University. There she partnered with community members and service providers to conduct a mixed methods study on pregnancy in homeless youth. This study utilized administrative data to estimate the rate of pregnancy in street youth and qualitative, in-depth interviews to understand how identity, isolation and belonging impacted the young women’s contraception and pregnancy-related decisions. Prior to working at PolicyWise, Allison was an Epidemiologist at Alberta Health, where she was involved in communicable disease surveillance, creating novel administrative data based vaccine efficacy estimates for the influenza vaccine, and developing and analyzing survey content to estimate the association between a history of homelessness and health. Allison loves to conduct policy-relevant research, travel and cook.


Mathematics with Computer Science
Students of mathematics learn to trace various problems back to mathematical models. At the same time, knowledge of programming is imparted in order to implement the models on the computer.
The course of studies Mathematics with Computer Science is free of admission.
Mathematics is a Bachelor's/Master's programme. In the Bachelor's programme, which regularly lasts 6 semesters, the student learns the basics of analysis, linear algebra, stochastics and discrete mathematics. In addition, he learns the basics of programming.
In the subsequent Master's programme, which regularly lasts 4 semesters, the student can deepen his or her skills and specialise
Mathematicians work in system and software development, in management consulting, at banks, credit institutions or insurance companies.
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Quantitative Economics, 2017
Abstract: Approximating stochastic processes by finite-state Markov chains is useful for reducing computational complexity when solving dynamic economic models. We provide a new method for accurately discretizing general Markov processes by matching low order moments of the conditional distributions using maximum entropy. In contrast to existing methods, our approach is not limited to linear Gaussian autoregressive processes. We apply our method to numerically solve asset pricing models with various underlying stochastic processes for the fundamentals, including a rare disasters model. Our method outperforms the solution accuracy of existing methods by orders of magnitude, while drastically simplifying the solution algorithm. The performance of our method is robust to parameters such as the number of grid points and the persistence of the process.
Abstract: Existing methods for estimating nonlinear dynamic models are either too computationally complex to be of practical use, or rely on local approximations which often fail adequately to capture the nonlinear features of interest. I develop a new method, the discretization filter, for approximating the likelihood of nonlinear, non-Gaussian state space models. I establish that the associated maximum likelihood estimator is strongly consistent, asymptotically normal, and asymptotically efficient. Through simulations I show that the discretization filter is orders of magnitude faster than alternative nonlinear techniques for the same level of approximation error and I provide practical guidelines for applied researchers. I apply my approach to estimate a New Keynesian model with a zero lower bound on the nominal interest rate. After accounting for the zero lower bound, I find that the slope of the Phillips Curve is 0.076, which is less than 1/3 of typical estimates from linearized models. This suggests a strong decoupling of inflation from the output gap and larger real effects of unanticipated changes in interest rates in post Great Recession data.
Abstract: Return predictability in the U.S. stock market is local in time as short periods with significant predictability ('pockets') are interspersed with long periods with little or no evidence of return predictability. We document this empirically using a flexible non-parametric approach and explore possible explanations of this finding, including time-varying risk-premia. We find that short-lived predictability pockets are inconsistent with a broad class of affine asset pricing models. Conversely, pockets of return predictability are more in line with a model with investors' incomplete learning about a highly persistent growth component in the underlying cash flow process which undergoes occasional regime shifts.


Remembering SHAKUNTALA DEVI – The Human Computer
CHILD PRODIGY and MATH GENIUS
Shakuntala Devi was born in Bengaluru, Karnataka State of India on November 4, 1929.
At age 3, it was while playing cards with her father, that he discovered her uncanny ability to memorize numbers.
She dropped out of school because her father, a circus worker, could not afford the monthly school fee of Rs 2.
Shakuntala Devi began demonstrating her math skills at the circus where her father worked as a performer and later in roadshows arranged by him after he quit the circus.
At age 6, she gave her first major show at the University of Mysore.
She became world-famous and she traveled the world, displaying her ability to perform complex calculations in her head, despite having no formal education.
During an event at the University of Rome, the judges declared her answer to a problem as wrong, until the experts re-examined their own calculations and found her to be wright.
FASTER THAN A COMPUTER
At an event in 1977, she extracted the 23rd root of a 201-digit number in just 50 seconds beating a Univac computer, which took 62 seconds.
She could mentally calculate the cube root of numbers as big as 204,336,469 in 5 seconds and give any date in the last century, she could ascertain the day on which it fell.
GUINNESS RECORD HOLDER
In 1980, she correctly multiplied two 13-digit numbers, given to her randomly by the computer department at the Imperial College in London, in only 28 seconds, earning her a place in 1982 Guinness Book World Records.
Shakuntala Devi’s record included the time it took her to recite the 26-digit solution.
AUTHOR AND MORE
She has written several books on math puzzles like ‘Puzzle to Puzzle You’ and also a book titled ‘The World of Homosexuals.” a compilation of her conducted interviews and research on homosexuality.
She was also a successful astrologer and cookbook author.
A LIFE LONG MATH LOVER
On April 21, 2013, at the age of 83, she passed away due to cardiac and respiratory problems.
She had once said
“Mathematics is life, you have math in everything, right from time to your date of birth to the food you eat and the air you breathe.”
Also Read: More stories about People


ASTANA – Kazakhstan’s school students have demonstrated high mathematics and science scores in the international assessment of knowledge. According to the results of the Trends in International Mathematics and Science Study (TIMSS) released at the end of November, Kazakhstan’s 13 and 14-year-old students showed excellent knowledge in science achievements taking eighth place and students aged 9-10 years ranked in 12th place in mathematics.
According to Kazakh Minister of Education and Science Yerlan Sagadiyev, the progress of the fourth-grade students is very impressive.
“Our students made a great gift for us ahead of the 25th anniversary of the Independence of Kazakhstan. Kazakhstan is listed among leaders for mathematics and science education. Kazakh students’ results became significantly higher than the TIMSS international average,” said Sagadiyev in a special video message distributed after the results were released.
Kazakh students have managed to leave behind peers from Portugal, the United States, Denmark, Lithuania, Finland, Poland, Australia and others in mathematics and science studies.
“Students took the eighth and 12th positions according to the global study of knowledge. The results of our pupils are comparable to Russian students. They are ahead of their peers from the U.S., the United Kingdom, Germany, Turkey and many other countries. The rankings covered pupils studying in the public, rural and small schools. We are convinced that our students are talented, and we all need to believe in our children,” Sagadiyev added.
Singapore, Hong Kong, South Korea, Chinese Taipei and Japan dominate the international rankings.
The TIMSS result, released Nov. 29, assessed 57 countries on their achievements from 2011 to 2015.
The TIMSS has been assessing 9-10 and 13-14-year-old pupils’ attainment in mathematics and science at the fourth and eighth grades since 1995. Released by the International Association for the Evaluation of Educational Achievement (IEA), the large scale international assessment measures trends in the world every four years. Monitoring provides an opportunity to track changes in educational achievements of students while moving from primary (fourth grade) to the secondary (eighth grade) school.
For the first time, Kazakhstan took part in the TIMSS study in 2007. As a result, Kazakh fourth-graders took fifth place out of 36 countries in mathematical literacy and the 11th place in sciences.
In addition, the Organisation for Economic Cooperation and Development’s (OECD) international scholastic study, the Programme for International Student Assessment (PISA), released Dec. 6, found that Kazakh students have achieved progress in all areas of study compared to PISA-2012 results.
Over half a million 15-year-olds from across the globe participated in the PISA tests.
The study is aimed at identifying students’ capacities to apply knowledge and skills in different situations for an adequate socialisation.
Nowadays, modern parents are trying to pay more attention to children and unveil their skills in various directions realising that rapidly developing world generates more challenges for younger people.
According to Assan Zholdassov, head of Pythagoras School, engaged in training competitive students in science, technology, mathematics and engineering, students tend to choose careers in technical areas.
“At present, great number of children show interest in mathematics and exact sciences.
Students like to compete; they are fond of solving mathematical tasks. Parents also make a great contribution to children’s study,” said Zholdassov in an interview to the Astana Times.
Based on the Kazakh-British Technical University (KBTU), the Pythagoras School opened in 2008 in Almaty. Recently, the school has provided pupils with a chance to be enrolled in its branches in Astana.
The school of additional education is included in the National Organising Committee of the world’s largest mathematics competitions such as the International Mathematics and Science Olympiad (IMSO) and the International Mathematics Competition (IMC). Just recently, the Pythagoras students brought 12 medals out of 12 possible from the IMC.
The Pythagoras school graduates won more than 700 medals at the national and international competitions.
“The state is paying particular attention to the education sector encouraging pupils to achieve higher results in different spheres,” he added.


There's a type of space-filling fractal curve called a Hilbert curve. In its mathematical form, it's an infinitely long line that winds its way around a finite space like a square.
In my recent tradition of trying All Sorts of Stuff on a laser cutter, I thought it might be interesting to cut a (finite) Hilbert curve into a sheet of paper with a laser cutter. This is the sort of thing that would take several days with an X-acto knife.
Now I have a square of paper that is only about 6x6 inches in size, but if I pulled the ends of it apart as far as they will go, it would be about 20 ft long.
I'm playing around with other forms of it to see if I can make a mobile:
- More fun with laser cutter... space filling curves.


Apr 18, 2024
Option in Mathematics Education for Secondary School Teachers is designed for people holding a California Single Subject Teaching Credential in Mathematics and teaching in middle, junior high, or high schools. This option will give students greater expertise in mathematics and mathematics education (curriculum, teaching, learning, assessment and research). The program includes a blend of courses from pure and applied mathematics, statistics, mathematics education, and also may include coursework from the College of Education.
A bachelor’s degree and a Single Subject Credential
- A bachelor’s degree in mathematics or mathematics education, or a bachelor’s degree with at least 24 upper division units in mathematics from an accredited college or university.
- A California Single Subject Credential in Mathematics.
A grade of “C” or better in the following courses
The following course work, or equivalent, with grades of C or better:
Advancement to Candidacy
In addition to University requirements stated elsewhere in this catalog, must have completed prerequisites above. Must file for Advancement to Candidacy after completion of at least 6 units (and recommend filing before completing 9 units) on Program of Study, with an overall 3.0 grade-point average. Program of Study must be approved by Mathematics Education Graduate Advisor, and Associate Dean in the College of Natural Sciences and Mathematics or designee.
A minimum of 30 units of graduate level or approved upper division coursework which includes the following:
A minimum of 9 graduate or approved upper-division units of mathematics, including at least one 500-level mathematics course. If not previously taken for BS or credential, this course of study must include:
A minimum of 15 graduate units of mathematics education including:
Take both of the following:
At least 9 units in mathematics education
At least 9 units in mathematics education chosen in consultation with the Mathematics Education Graduate Advisor from the following courses:
A minimum of 6 units of approved upper division or graduate electives
A minimum of 6 units of approved upper division or graduate electives from mathematics, mathematics education, statistics, or approved College of Education courses, chosen in consultation with the Mathematics Education Graduate Advisor.
Complete one of the following two options:
Pass two comprehensive written examinations in mathematics education
And one in a selected area
Subject to the approval of the Mathematics Education Committee of the Department of Mathematics and Statistics, write a thesis in mathematics education and defend it orally
Mathematics Education Thesis
Students choosing the thesis option must consult with the Mathematics Education Graduate Advisor to select a thesis advisor. A proposal is then written in consultation with the mathematics education faculty advisor who will guide the student in choosing the thesis topic and supervise the writing process. After a thesis topic is chosen, it must be approved by the Mathematics Education Committee. A thesis committee of three faculty members, including the thesis advisor, is then chosen to approve the final work. During the writing of the thesis report, students must enroll in MTED 698.


I have a full day of pattern math ahead of me to get ready for this to be sent off to the tech editor:
Don’t tell anyone, but I secretly find pattern math fun.
woo hoo! i love love love that yellow sweater! best of luck with your math. )
Love it! Hope it will be available to buy soon!
I find it fun, too.
I love the bright contrast buttons on the bright sweater.
Math and I are not friends. I’d rather make friends with your cardigan. Did I tell you how much I adore quarter length sleeves?
The yellow sweater is fabulous! I do not like pattern math. :/
I just love this sweater. This color yellow is so bright and inviting and just begs to be worn often.
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