About this app

This app performs one of the most common and important statistical tests, the t-test for independent groups. It determines whether any two groups' means are significantly different from each other beyond simply chance differences. The statistical design associated with the t-test for independent groups is that subjects are randomly assigned to two groups. One of the groups (i.e., experimental group) receives a special treatment, therapy, or drug. The other group doesn't receive that treatment but gets a placebo (i.e., that group is called the control group or placebo group). Both groups are then measured on some outcome variable (or response variable) which is designed to measure whether the treatment , therapy, or drug works beyond chance. The t-test for independent groups then computes a probability statistic which determines whether the two groups means are different beyond chance. Depending on the pattern of mean differences, it may be concluded that the new treatment, therapy or drug is beneficial, harmful, or has no effect (beyond chance). The experimental design and statistical procedure for the t-test for independent groups makes it the most powerful research procedure in almost all disciplines of the natural and social sciences, especially medical research and psychology. The t-test for independent groups procedure calculates a final probability to the conclusion: if the differences in means are deemed to be beyond what would be expected by chance, then p < .05 appears, which means that the probability is less than 5 chances out of 100 that the experimenter is wrong. In this case, the means are deemed statistically significant. If the probability statistic deems the mean differences are due to chance, then the t-test for independent groups attaches p > .05 and the differences are deemed to be not statistically significantly different or non-significantly different.

New features

Added Chi-Square Test: 2 x 2 Design.

App Permissions

Allows applications to open network sockets.