One Numerical Variable

  • This activity uses Microsoft Excel to estimate the population variance of grouped data two ways: the variance within a group and the variance between groups. This activity accompanies Section 7.3 of Data Matters.
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  • This is a collection of activities as Java applets that can be used to explore probability and statistics. Each activity is supplemented with background information, activity instructions, and a curriculum for the activity.
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  • This worksheet activity teaches random sampling and theoretical probabilities by simulating the effects of randomly assigning newborn babies to their mothers. Students will perform trials and keep track of results, then use the information to deduce properties of random sampling. The relation website is an applet that simulates the process automatically.
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  • This collection of calculators allows users to perform a number of statistical applications. Each provides background on the procedure and an example. Users can compute Descriptive Statistics and perform t-tests, Chi-square tests, Kolmogorov-Smirnov tests, Fisher's Exact Test, contingency tables, ANOVA, and regression.

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  • A short discussion of what outliers are and their helpfulness in analyzing data.
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  • This text document lists detailed learning objectives for introductory statistics courses. Learning objectives are brief, clear statements of what learners will be able to perform at the end of a course. These objectives were developed for a one semester general education introductory statistics course. The objectives cover the broad categories of Graphics, Summary Statistics, The Normal Distribution, Correlation and Scatterplots, Introduction to Regression, Two way Tables, Data Collection and Surveys, Basic Probability, Sampling Distributions, Confidence Intervals, Tests of Hypothesis, and T-distributions.
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  • Users can select from detailed tables and geographical comparison tables to generate data from the 2000 Census.
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  • an old "walks into a bar" joke with a statistics twist.

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  • This general, introductory tutorial on mathematical modeling (in pdf format) is intended to provide an introduction to the correct analysis of data. It addresses, in an elementary way, those ideas that are important to the effort of distinguishing information from error. This distinction constitutes the central theme of the material described herein. Both deterministic modeling (univariate regression) as well as the (stochastic) modeling of random variables are considered, with emphasis on the latter. No attempt is made to cover every topic of relevance. Instead, attention is focussed on elucidating and illustrating core concepts as they apply to empirical data.

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  • This set of exercises asks students to model relationships and test them based on the chi-square distribution. The data used is based on testosterone levels and delinquency rate of American military men.
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