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 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.
This page generates a graph of the sampling distribution of r, the Pearson correlation coefficient. Upon opening, the applet prompts for sample size greater than 6. The applet also displays the probabilities associated with the distribution.
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 calculates the point biserial correlation coefficient for the case where one variable is dichotomous and the other is non-dichotomous. This page allows the user to input the data directly or copy and paste from a spreadsheet application and provides data summary.
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.
In the first simulation, random samples of size n are drawn from the population one sample at a time. With df=3, the critical value of chi-square for significance at or beyond the 0.05 level is 7.815; hence, any calculated value of chi-square equal to or greater than 7.815 is recorded as "significant," while any value smaller than that is noted as "non-significant." The second simulation does the same thing, except that it draws random samples 100 at a time. The Power of the Chi-Square "Goodness of Fit" Test pertains to the questionable common practice of accepting the null hypothesis upon failing to find a significant result in a one- dimensional chi-square test.
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.
This page will calculate r_s , the Spearman rank- order correlation coefficient, for a bivariate set of paired XY rankings. As the page opens, you will be prompted to enter the number of items for which there are paired rankings. If you are starting out with raw (unranked) data, the necessary rank-ordering will be performed automatically.