This page calculates the standard error of a sampling distribution of sample means when users input the mean and standard deviation of the population and the sample size.
This page calculates the standard error of a sampling distribution of sample means when users input the mean and standard deviation of the population and the sample size.
This textbook from VassarStats introduces various statistical topics and contains interactive components. Topics include: Measurement Principles; Distributions; Correlation; Regression; Partial Correlation; Rank-Order Correlation; Statistical Significance; Sampling Distributions; Hypothsis Tests; Probability; Chi-Square; Fisher's Exact Test; t-Distribution; t-test; Mann-Whitney Test; Wilcoxon Signed-Rank Test; Analysis of Variance; F-Distribution; Kruskal-Wallis Test; Friedman Test; Analysis of Covariance. Several calculators and generators include: Binomial Probability; Normal Probability; Binomial Sampling Distribution; Chi-Square Sampling Distribution.
Illustrates the central limit theorem by allowing the user to increase the number of samples in increments of 100, 1000, or 10000.
This page generates a graph of the Chi-Square distribution and displays the associated probabilities. Users enter the degrees of freedom (between 1 and 20, inclusive) upon opening the page.
This applet generates a graph of the sampling distribution of sample means and displays the probabilities associated with that distribution. Users enter the mean and standard deviation of the source population and the size of the samples. The applet also calculates the standard error of the sample means.
An application of Bayes Theorem that performs the same calculations for the situation where the several probabilities are constructed as indices of subjective confidence.
This page will generate a graphic and numerical display of the properties of a binomial sampling distribution, for any values of p and q, and for values of n between 1 and 40, inclusive.
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.
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.
The page will calculate the following: Exact binomial probabilities, Approximation via the normal distribution, Approximation via the Poisson Distribution. This page will calculate and/or estimate binomial probabilities for situations of the general "k out of n" type, where k is the number of times a binomial outcome is observed or stipulated to occur, p is the probability that the outcome will occur on any particular occasion, q is the complementary probability (1-p) that the outcome will not occur on any particular occasion, and n is the number of occasions.