This lesson on the Poisson distribution explains the theory, history, and applications of the distribution and gives examples and a multiple choice test.
This page will calculate the lower and upper limits of the 95% confidence interval for a proportion, according to two methods described by Robert Newcombe, both derived from a procedure outlined by E. B. Wilson in 1927. The first method uses the Wilson procedure without a correction for continuity; the second uses the Wilson procedure with a correction for continuity.
This page will calculate the lower and upper limits of the 95% confidence interval for the difference between two independent proportions, according to two methods described by Robert Newcombe, both derived from a procedure outlined by E.B.Wilson in 1927. The first method uses the Wilson procedure without a correction for continuity; the second uses the Wilson procedure with a correction for continuity.
Given two independent samples of sizes n_a and n_b, this page will estimate the significance of the difference between the means of the samples, based on multiple random re-sortings of the values that have been entered for samples A and B. As the page opens, you will be prompted for the sizes of the two samples.
This page will perform the procedure for up to k=12 sample values of r, with a minimum of k=2. It will also perform a chi-square test for the homogeneity of the k values of r, with df=k-1. The several values of r can be regarded as coming from the same population only if the observed chi-square value proves the be non-significant.
This calculator returns the value of t for the difference between the means of two correlated samples, for sample sizes up to 10. Users are prompted for sample size as the page opens. It will also calculate various summary statistics for the two samples.
As the page opens, you will be prompted to enter two sample size values, na and nb. If the samples are of different sizes, the larger of the two should be designated as sample A. If you are starting out with raw (unranked) data, the necessary rank- ordering will be performed automatically.
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