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  • This site offers an involved definition of the likelihood ratio test with examples and formulas.
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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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  • The eighth chapter of an online Introduction to Biostatistics course. Lecture notes are provided. Additionally, links for additional reading and exercises with solutions are provided.
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  • The online "Engineering Statistics Handbook" provides a section (4.6 Case Studies in Process Modeling) using detailed realistic examples from physical science and engineering applications. Examples in Load Cell Calibration, Alaska Pipeline Ultrasonic Calibration, Ultrasonic Reference Block Study, and Thermal Expansion of Copper Case Study are presented in a step-by-step manner.
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  • This case study explores statistics on divorce rates using Markov chains. Two closely related statistics are presented: the chance of divorcing in a given year and the chance of divorcing over the lifetime of a marriage. Accompanying teacher instructions are found at http://ublib.buffalo.edu/libraries/projects/cases/markov/markov_notes.html
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  • This article gives a description of typical sources of error in public opinion polls. It gives a short but insightful explanation of what the margin of error indicates as well as other common errors in opinion polls.
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  • This source defines and explains variance and standard deviation.
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  • Part of an online statistics textbook. Topics include: (1) Law of Large Numbers for Discrete Random Variables, (2) Chebyshev Inequality, (3) Law of Averages, (4) Law of Large Numbers for Continuous Random Variables, (5) Monte Carlo Method. There are several examples and exercises that accompany the material.
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  • This resource defines what a p-value is, why .05 is significant, and when to use it. It also covers related topics such as one-tailed/two-tailed tests and hypothesis testing.
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  • In this activity, students work in groups to provide practical interpretations of graphs, considering shape, center, and spread. Each group posts their interpretation for one graph and critiques other groups' interpretations on other graphs. Students examine key aspects (shape, spread, location, etc) of histograms and stem plots to develop the ability to interpret graphics. This activity gets the students up and out of their seats and working together. It is a good activity for early in a term. The Gallery Walk idea can be adapted for different sized classes but this activity has been designed for classes up to 65 students.
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