Categorical Methods

  • 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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  • This case study covers the following concepts: confidence intervals for proportions and the normal approximation to the binomial. It also assesses the question: "What proportion of the iMac purchasers are new computer owners?"
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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 free online video program "marks a transition in the series: from a focus on inference about the mean of a population to exploring inferences about a different kind of parameter, the proportion or percent of a population that has a certain characteristic. Students will observe the use of confidence intervals and tests for comparing proportions applied in government estimates of unemployment rates."
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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 tutorial on Multiple Regression helps students understand the definition, use the standard error of estimate, use rank correlation, and solve exercise problems using multiple regression.
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  • This interactive tutorial on Exponential Smoothing helps learners understand the use of exponential smoothing, define exponential smoothing, cite the merits and demerits of exponential smoothing, and solve exercise problems using exponential smoothing.
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  • This interactive module helps students to understand the definition of and uses for clustering algorithms. Students will learn to categorize the types of clustering algorithms, to use the minimal spanning tree and the k-means clustering algorithm, and to solve exercise problems using clustering algorithms.
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  • The Data Library contains lists of ongoing data-sharing projects, downloadable data sets in Excel spreadsheet format, and other sources of data found on the web.
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