Data Presentation

  • 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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  • This site discusses types of data, stem and leaf plots, mean and median, histograms, and barcharts. Exercises are also provided, as well as their corresponding answers.
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  • This exercise includes a discussion on comparing data with very different sample sizes and nonhomogeneity of variance. The data comes from a study on the behavior of pregnant women with regard to cigarette smoking.
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  • This lesson describes bootstrapping in the context of a statistics class for psychology students.
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  • This excerpt from Engineering Statistics Handbook gives a definition for and examples of outliers. A sub-page also discusses Grubbs' Test for Outliers
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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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  • This random number generator produces a data table with up to 10 columns and up to 2500 rows. For random integers, users must specify the data range. For data from a Normal (Gaussian) distribution, users specify mean and standard deviation.

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