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Association & Odds Ratios

  • This simulation illustrates types of sums of squares in a 2 x 3 ANOVA.
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  • This case study assesses the question, "Can the application of magnetic fields be an effective treatment for pain?" It addresses concepts including: boxplots, stem and leaf displays, correlated t-test, two-sample t-test, repeated measures analysis of variance, and analysis of covariance.
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  • This case study compares a low-fat diet to a "Mediterranean diet" to see which led to better health. Concept: Chi Square test of independence
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  • In this free online video program, "students will understand inference for simple linear regression, emphasizing slope, and prediction. This unit presents the two most important kinds of inference: inference about the slope of the population line and prediction of the response for a given x. Although the formulas are more complicated, the ideas are similar to t procedures for the mean sigma of a population."

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  • This tutorial on Distributions helps students understand the basic concept of probability distributions, recognize and use Binomial, Normal, Poisson, and Uniform Distributions, and solve exercise problems using probability distributions.
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  • This chapter of the NIST Engineering Statistics handbook describes Exploratory Data Analysis with an introduction, a discussion of the assumptions, a description of the techniques used, and a set of case studies.
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  • This site contains lessons which include steps, examples, and a calculator, on standard deviation, Pearson's r, t-test, one-way ANOVA, and Tukey's Post Hoc Test.
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  • This site gives an explanation, a definition and an example of two-way tables and the chi-square test. Topics include: categorical data analysis for two variables, and tests of association.
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  • This chapter of the "Concepts and Applications of Inferential Statistics" online textbook describes in detail the Kruskal-Wallis test, it's formulas, variables, and procedures using an example involving wine-tasters.

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  • Explains how to set up the Kruskal-Wallis test and gives the formula for the test statistic.
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