Expectations

  • The Journal of Statistics Education has published this collection of datasets and related articles describing their use, submitted by faculty members from numerous institutions. Data is in .dat format.
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  • This collection is organized as discussions and activities in the subjects of descriptive statistics, inferential statistics, graphical analysis, and TI-83 and Excel guides. It also includes a section of quizzes. Key Words: Mean; Median; Mode; Normal Distribution; Skewed Distribution; Range; Standard Deviation; Confidence Interval; T-Test; ANOVA; Correlation; Regression; Chi-Square; Probability Distributions; Histograms; Scatterplots; Boxplot.
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  • In this activity, students will calculate the mean, median, and mode of the salaries for the Angels and the Orioles baseball players. Questions about the exercise and links to Excel and TI-83 instructions. The data exists in Excel, TI-83, and text formats.
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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 free online video program "explains the basic reasoning behind tests of significance and the concept of null hypothesis. The program shows how a z-test is carried out when the hypothesis concerns the mean of a normal population with known standard deviation. These ideas are explored by determining whether a poem "fits Shakespeare as well as Shakespeare fits Shakespeare." Court battles over discrimination in hiring provide additional illustration.
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  • In this free online video program, "students will learn to derive and interpret the correlation coefficient using the relationship between a baseball player's salary and his home run statistics." The students will then "discover how to use the square of the correlation coefficient to measure the strength and direction of a relationship between two variables. A study comparing identical twins raised together and apart illustrates the concept of correlation."
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  • This site gives an explanation, a definition and an example of correlation. Topics include correlation coefficient and rŒ_.

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  • This site gives an explanation of, an example of, and a definition for binomial distributions including counts, proportions, and normal approximation.
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  • These pages will perform an analysis of covariance for k independent samples, where the individual samples, A, B, etc., represent k quantitative or categorical levels of the independent variable; DV = the dependent variable of interest; and CV = the concomitant variable whose effects one wishes to bring under statistical control. The pages in this first batch require the direct entry of data, item by item, and as they open you will be prompted to enter the size of the largest of your several samples. The pages in this second batch allow for the import of data from a spreadsheet via copy and paste procedures.

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