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  • IDEAL: The Normal Distribution

    This module discusses the history and importance of the normal distribution, as well as normal moments, the standard normal distribution, normal probabilities, Z-Scores, and normal quantiles. The applet allows users to compute normal probabilities and quantiles. Three follow-up examples cover cholesterol, male heights, and mean temperatures for various cities in South Carolina.

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  • Dataset: Exploratory Teratology Study in Rats

    This dataset comes from a study on pregnant rats. Forty rats were given 4 doses of a drug, and data on their fetuses were collected. Questions this study focused on refer to the relationship between dosage of the drug and gender of the fetus. A text file version of the data is found in the relation link.

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  • Statistical Literacy Curriculum Design

    A specially-designed statistical literacy course is needed for college students in majors that don't require statistics or mathematics. This paper suggests that key topics in conditional probability, multivariate regression and the vulnerability of statistical significance to confounding should be included and presents some new ways to teach these ideas.

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  • Hypothesis Testing

    This PowerPoint lecture presentation discusses comparing the means of two dependent populations using the paired T-test and defines the concepts of this hypothesis test. The original presentation is available for downloading.

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  • Selective Attention: Gorilla Video

    This video is an example of what is known in psychology as selective attention. When a person is instructed to only focus on the number of times a ball is passed between players wearing a white shirt it is sometimes difficult to see what else is going on.

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  • **Type I and Type II Errors - Making Mistakes in the Justice System

    This webpage uses the criminal trials in the US Justice system to illustrate hypothesis testing, type I error, and type II error. An applet allows the user to examine the probability of type I errors and type II errors under various conditions. An applet allows users to visualize p-values and the power of a test. Keywords: type I error, type II error, type one error, type two error, type 1 error, type 2 error

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  • Can a difference be important if it is not significant?

    This short article discusses the difference between "important" and "statistically significant." The data used come from a study comparing male faculty salaries to female faculty salaries.

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  • The Statistics of Hiring

    This short article discusses how the comparative ratios of the tails of normal distributions can result in bias in hiring practices. It contains a link to an applet that shows the comparative tail probability ratios.

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  • Dataset: Rock Fries Your Brains

    This exercise uses descriptive statistics to analyze a data set about how rats respond to rock music vs. classical music.

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  • How Random is Random?

    This site is a tutorial that takes students through a mayoral election process while discussing the concept of randomness. Topics include margin of error and confidence levels.

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