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  • A "12 page" tutorial that explores the liner models via excel spreadsheets. The learning module leads the user through various aspects of linear modeling. This tutorial includes a worksheet that allows students to vary the scatter (or noise) level, by adjusting the scroll bar or by clicking on the arrows, to see how the slope and intercept of line respond to the addition of scatter to the data, while monitoring the value of r^2.

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  • This course website provides materials for teaching and learning path analysis. Materials include Regression Review, Introduction to Path Notation, Standardized Path Models, Unstandardized Path Models, Matrix Algebra, and many SAS programs.
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  • This tutorial explains the theory and use of the Chi-Square Test for goodness of fit and demonstrates it with an example on mastery test scores. Data is given as well as SPSS and Minitab code.
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  • This case study covers the concepts including: boxplots, stem and leaf displays, two-sample t tests, and analysis of variance. It also assesses the question, "Does an instructor's reputation affect ratings of the instructor's lecture?"
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  • The applet allows users to sample from a normal distribution or from a uniform distribution. It shows the expected values and the observed values and computes the deviation. Then, a chi-square test shows if the deviations are significant for both the normal and uniform distributions.
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  • This site provides a PowerPoint presentation of a lesson and examples of relative risks and odds ratios.
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  • The goal of this handbook is to help scientists and engineers incorporate statistical methods in their work as efficiently as possible.
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  • This page, part of the NIST Engineering Statistics handbook, describes the Kolmogorov-Smirnov goodness of fit test. It contains a graph of the empirical distribution function with the cumulative distribution function, a definition of the test, the questions it answers, the assumptions that it makes, and links to other goodness of fits tests and a case study.
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  • This online, interactive lesson on point estimation provides examples, exercises, and applets concerning estimators, method of moments, maximum likelihood, Bayes estimators, best unbiased estimators, and sufficient, complete and ancillary statistics.
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  • This online, interactive lesson on random samples provides examples, exercises, and applets concerning sample mean, law of large numbers, sample variance, partial sums, central limit theorem, special properties of normal samples, order statistics, and sample covariance and correlation.
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