Linear Models

  • This applet allows the user to simulate a race where the results are based on the roll of a die. The user can determine which player moves forward for a given roll, and can then experiment with the race by determining which player will win more often based on the rules that they specify.

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  • This applet is designed to teach an application of probability. This java applet works by simulating a situation where a three stage rocket is about to be launched. In order for a successful launch to occur all three stages of the rocket must successfully pass their pre-takeoff tests. By default, each stage has a 50% chance of success, however, this can be altered by dragging the bar next to each stage.
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  • In this applet, we simulate a series of hypothesis of tests for the value of the parameter p in a Bernoulli random variable. Each column of red and green marks represents a sample of 30 observations. "Successes'' are coded by green marks and "failures'' by red marks.

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  • This applet simulates rolling dice to illustrate the central limit theorem. The user can choose between 1, 2, 6, or 9 dice to roll 1, 5, 20, or 100 times. The distribution is graphically displayed. This applet needs to be resized for optimal viewing.

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  • This page will perform an analysis of variance for the situation where there are three independent variables, A, B, and C, each with two levels. The user may enter data directly or copy and paste from a spreadsheet or other application.

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  • This page will compute the One-Way ANOVA for up to five samples. The design can be either for independent samples or correlated samples (repeated measures or randomized blocks). This page will also perform pair-wise comparisons of sample means via the Tukey HSD test

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  • This page will perform a two-way factorial analysis of variance for designs in which there are 2-4 levels of each of two variables, A and B, with each subject measured under each of the AxB combinations.

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  • This page will perform a two-way factorial analysis of variance for designs in which there are 2-4 randomized blocks of matched subjects, with 2-4 repeated measures for each subject.

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  • This page will compute the Two-Way Factorial ANOVA for Independent Samples, for up to four rows by four columns. This page will also calculate the critical values of Tukey's HSD for purposes of post-ANOVA comparisons.

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  • The following pages calculate r, r-squared, regression constants, Y residuals, and standard error of estimate for a set of N bivariate values of X and Y, and perform a t-test for the significance of the obtained value of r. Allows for import of raw data from a spreadsheet; for samples of any size, large or small.

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