Simulation

  • This article presents a dataset containing actual monthly data on computer usage in Best Buy stores from August 1996 to July 2000. This dataset can be used to illustrate time-series forecasting, causal forecasting, simple linear regression, unequal error variances, and variable transformation. Key Words: Model-building; Seasonal Variation.
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  • The dataset presented in this article comes from a South African study of growth of children. This data is a useful example of Simpson's paradox. Key Words: Categorical data; Comparing proportions.
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  • This article presents a dataset containing physical measurements for 507 physically active individuals. These data can be used to demonstrate simple descriptive statistics, least squares and multiple regression, or discriminant and classification analysis. The data are in .dat format.
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  • This site provides applets, lessons, and objectives for learning about conditional probability. The applet activity introduces multiple-outcomes events and computing probabilities.
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  • This site provides numerous datasets for graphical display topics including linear, exponential, logistic, power rule, periodic, and other bivariate scatterplots, histograms, and other univariate data. Each data set is accompanied with a description, file format options, and a sample graph.
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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 applet simulates randomly assigning newborn babies to families and measures the number of matches, or instances when a baby is assigned to its real family. The applet keeps track of each trial and records the information in a histogram. The idea is to teach theoretical values associated with random sampling. The relation website is a worksheet activity to accompany the applet.
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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 applet performs a hypothesis test for the mean of a single normal population, variance known. Users set the hypothesized mean, true mean, variance, and appropriate alternative hypothesis. The applet plots a representative distribution under the given values with power shaded in blue and significance level shaded in red.
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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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