This applet demonstrates the partitioning of sums of squares in analysis of variance (ANOVA). It includes some sample values and allows the user to make adjustments, which then shows the new values in the ANOVA table. Also contains an exercise set.
This applet demonstrates the partitioning of sums of squares in analysis of variance (ANOVA). It includes some sample values and allows the user to make adjustments, which then shows the new values in the ANOVA table. Also contains an exercise set.
This collection of Analysis Tools can assist students and researchers with questions about study desgin, data analysis, and probability. Topics include sample size, power, survival, binomial probabilities, interaction, Fisher's exact test, one and two sample tests, and more.
This resource defines a pie chart. It also allows the user to input values to create their own graphs. The user has control over the title, up to 15 slices, the color of each slice, and can choose a 3-D option.
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.
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.
This page will calculate the intercorrelations (r) for any number of variables (V1, V2, V3, etc.) and for any number of observations per variable.
This page will calculate the intercorrelations (r and r2) for up to five variables, designated as A, B, C, D, and E.
This page has two calculators. One will cacluate a simple logistic regression, while the other calculates the predicted probability and odds ratio. There is also a brief tutorial covering logistic regression using an example involving infant gestational age and breast feeding. Please note, however, that the logistic regression accomplished by this page is based on a simple, plain-vanilla empirical regression.
In the Latin Square computational pages on this site, the third IV, with levels designated as A, B, C, etc., is listed as the "treatment" variable. The analysis of variance within an orthogonal Latin Square results in three F-ratios: one for the row variable, one for the column variable, and one for the third IV whose j levels are distributed orthogonally among the cells of the rows x columns matrix.
In the Latin Square computational pages on this site, the third IV, with levels designated as A, B, C, etc., is listed as the "treatment" variable. The analysis of variance within an orthogonal Latin Square results in three F-ratios: one for the row variable, one for the column variable, and one for the third IV whose j levels are distributed orthogonally among the cells of the rows x columns matrix.