There are a number of different types of hypothesis tests, useful for different hypothesis scenarios and data samples. The most commonly used are:

**Normality:**tests for normal distribution in a population sample.**T-test:**tests for a Student’s t-distribution – ie, in a normally distributed population where standard deviation in unknown and sample size is comparatively small. Paired t-tests compare two samples.**Chi-Square Test for Independence:**tests for an association of significance between two categorical variables in a population sample. Typically used with random sampling.**Homogeneity of Variance (HOV):**tests the similarity of dispersion parameters in two or more population samples.**Analysis of Variance (ANOVA):**tests for and analyzes differences between the means in several groups. Often used similarly to a t-test, but for more than two groups.**Mood’s Median:**compares the medians of two or more population samples.**Welch’s T-test:**tests for equality of means between two population samples. Also known as*Welch’s unequal variances t-test*.**Kruskal-Wallis H Test:**compares two or more groups with an independent variable, based on a dependent variable. Also known as*one-way ANOVA on ranks*.**Box-Cox Power Transformation:**transforms a data set into normal distribution.