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Correlation

  • These pages explain the following basic statistics concepts: mean, median, mode, variance, standard deviation and correlation coefficient (with example from the Institute on Climate and Planets).

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  • This presentation is a part of a series of lessons on the Analysis of Categorical Data. This lecture covers the following: linear association, correlation coefficient, ridits/modified ridits, nonparametric methods, Cochran-Armitage Trend test, 

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  • This text explains the differences between t-tests, z-tests, tests with proportions, and tests of correlation.

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  • The applets in this section allow you to see how different bivariate data look under different correlation structures. The Movie applet either creates data for a particular correlation or animates a multitude data sets ranging correlations from -1 to 1. The Creation applet allows the user to create a data set by adding or deleting points from the screen. This page was formerly located at http://www.stat.vt.edu/~sundar/java/applets/Correlation.html
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  • Each dataset in this collection includes description of the study, description of the data file, statistical topic covered, and reference. Topics addressed include: correlation, one-way ANOVA, Bonferroni multiple comparison procedure, regression (simple, multiple, and loglinear), chi-square, and the t-test.
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  • This page is a collection of examples, demonstrations, and exercises that can be used to motivate a lecture, demonstrate an important point, or create a laboratory exercise for students. Topics include the following: Descriptives, Normal Distribution, Sampling Distributions, Probability, Chi-Square, t tests, Power, Correlation/Regression, One-way Anova, Multiple Comparisons, Factorial Anova, Repeated Measures, Multiple Regression, General Linear Model, Log Linear Models, and Distribution-Free Tests.
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  • This free online video program "explains the basic reasoning behind tests of significance and the concept of null hypothesis. The program shows how a z-test is carried out when the hypothesis concerns the mean of a normal population with known standard deviation. These ideas are explored by determining whether a poem "fits Shakespeare as well as Shakespeare fits Shakespeare." Court battles over discrimination in hiring provide additional illustration.
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  • In this free online video program, "students will learn to derive and interpret the correlation coefficient using the relationship between a baseball player's salary and his home run statistics." The students will then "discover how to use the square of the correlation coefficient to measure the strength and direction of a relationship between two variables. A study comparing identical twins raised together and apart illustrates the concept of correlation."
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  • This site gives an explanation, a definition and an example of correlation. Topics include correlation coefficient and rŒ_.

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  • This site gives an explanation of, an example of, and a definition for binomial distributions including counts, proportions, and normal approximation.
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