In a normal distribution, the mean, median, and mode are all equal to the same value.

The probability of an event occurring can never be less than 0 or greater than 1.

The null hypothesis is the hypothesis that is being tested, while the alternative hypothesis is the hypothesis that is being proposed as an alternative to the null hypothesis.

The p-value is the probability of obtaining a test statistic as extreme as, or more extreme than, the observed test statistic, assuming that the null hypothesis is true.

In a regression analysis, the dependent variable is the variable that is being predicted, while the independent variable is the variable that is being used to predict the dependent variable.

The coefficient of determination (R^2) is a measure of how well the regression model fits the data, ranging from 0 to 1, with higher values indicating a better fit.

In a chi-square test, the expected frequencies are calculated by multiplying the row and column totals.

The t-test is used to compare the means of two independent groups, while the paired t-test is used to compare the means of two related groups.

The F-test is used to compare the variances of two independent groups.

The analysis of variance (ANOVA) is used to compare the means of more than two groups.

The Kruskal-Wallis test is a non-parametric test that is used to compare the medians of more than two groups.

The Mann-Whitney U test is a non-parametric test that is used to compare the medians of two independent groups.

The Wilcoxon signed-rank test is a non-parametric test that is used to compare the medians of two related groups.

The Spearman's rank correlation coefficient is a non-parametric measure of the correlation between two variables.

The Kendall's tau correlation coefficient is a non-parametric measure of the correlation between two variables.