Data Presentation

  • This case study assesses the question, "Is it easier to learn to use computer software that uses natural language commands?" Concepts: analysis of covariance, adjusted means, boxplots
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  • This case study assesses the question, "Do physicians discriminate against overweight patients?" This study indicates that, at least in one respect, they do. Concepts: t-test, means, boxplots
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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 free online video program "presents a detailed case study of statistics at work. Operating in a real-world setting, the program traces the practice of statistics - planning the data collection, collecting and picturing the data, drawing inferences from the data, and deciding how confident we can be about our conclusions. Students will begin to see the full range and power of the concepts and techniques they have learned." This individual video is accessed by scrolling down to the "Individual Program Descriptions - 26. Case Study " and click the "VOD" icon at the top-right of the description.
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  • This interactive tutorial on Basic Probability helps students understand the basic concepts of probability, define independent and compound events, use the basic properties of probability, understand the concept of conditional probability, and solve exercise problems using basic probability.
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  • This tutorial on Random Variables helps students understand the definition of random variables, recognize and use discrete random variables, recognize and use continuous random variables, and solve exercise problems using random variables.
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  • This interactive tutorial on Expectations helps students understand the concept of expectations, recognize and use variance and standard deviation, understand the method of moments, recognize and use co-variance, and solve exercise problems using expectations.
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  • This self-test provides a review/assessment of the Probability section of this module. At the bottom, there is a grading button to rate the users' understanding of the material.
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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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