Concept: Test Categories¶
Dataiku DSS groups hypothesis tests into categories based on different test attributes.
1. One-sample, Two-sample, and N-sample Tests¶
One-sample tests consider one population from which a random sample is used to make inferences.
Two-sample tests consider two populations from which independent random samples are used to make inferences.
N-sample tests consider more than two populations with independent random samples that are used to make inferences.
2. Location or Distribution Tests¶
Location tests evaluate hypotheses about location parameters. For example, the mean of a population (in the case of the one-sample Student’s t-test), and the median of a population (in the case of the Sign test).
Distribution tests evaluate hypotheses about population distributions. For example, one-sample distribution tests compare the distribution of a population to a hypothesized one, and two-sample distribution tests compare the distributions of two populations.
3. Categorical Tests¶
DSS provides the Chi-square Independence test, to evaluate whether two categorical variables are independent.
Additional Test Details¶
Finally, the header of a hypothesis test card contains a question icon that provides additional details about the test. More specifically, DSS displays if the test is a parametric or nonparametric test.