Beginning with a set of n paired values of Xa and Xb, this page will perform the necessary rank- ordering along with all other steps appropriate to the Wilcoxon test. As the page opens, you will be prompted to enter the number of paired values of Xa and Xb.
This page generates a Poisson distribution, as approximated by the Binomial. After clicking continue, users must enter the sample size (n>39) and probability of success (between 0.0 and 0.2, inclusive). A graph of the Poisson distribution with mean=np is shown as well as a table of the Poisson probabilities. Key Word: Poisson Calculator.
This page generates a histogram of a Poisson distribution and the associated table of probabilities. Upon opening the page, users will be prompted to enter the mean of the distribution (between 0.01 and 20.0, inclusive). Key Word: Poisson Calculator.
The page displays the sampling distribution and the standard error of the difference between two sample means. To calculate standard error, enter the standard deviation of the source population, along with the sample sizes, Na and Nb, and then click "Calculate".
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.
Calculates the areas under the curve of the normal distribution falling to the left of -z, to the right of +z, and between -z and +z.
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.
Using the Fisher r-to-z transformation, this page will calculate a value of z that can be applied to assess the significance of the difference between r, the correlation observed within a sample of size n and rho, the correlation hypothesized to exist within the population of bivariate values from which the sample is randomly drawn. If r is greater than rho, the resulting value of z will have a positive sign; if r is smaller than rho, the sign of z will be negative.
To assess the significance of any particular instance of r, enter the values of N[>6] and r into the designated cells, then click the 'Calculate' button. Application of this formula to any particular observed sample value of r will accordingly test the null hypothesis that the observed value comes from a population in which rho=0.