Correlation

  • As described in the web page itself: "This document was prepared as an illustration of the use of both t tests and correlation/regression analysis in drawing conclusions from data in an actual study." The study compares athletic performance of swimmers that are optimists vs. pessimists.
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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 page has data sets used by UCLA statistics classes. The html files in the second column contain descriptions of a particular data set and a link to the data at the end of the file. There are also .dat and .dta files that contain just data, with no description.
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  • This page discusses disadvantages of large datasets with regard to Simpson's Paradox.
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  • This page contains information and links about statistical literacy. Some links are to textbooks, online articles, resources, and information about upcoming events.
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  • This module contains discussions on t-test, ANOVA, correlation, two-way factorial ANOVA, regression, chi-squared, and distributions and provides links to a variety of activities relevant to the discussions.
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  • In this activity, students will calculate the correlation between GPA and SAT scores on 1000 students. The dataset contains high school GPA, college GPA, and SAT score for each student. Questions about the exercise and a link to Excel instructions are given. The data exist in Excel and text formats.
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  • In this activity, students will calculate the correlation between the ratio of doctors to people and the average lifespan for 40 countries. The dataset contains the name of the country, the number of citizens per doctor, and the average female lifespan (in years). Questions about the exercise and a link to Excel instructions are given. The data exist in Excel data format and text format.
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