Qualitative data can be categorized into groups. It represents characteristics or attributes and is often categorized or grouped. For example, hair color (blonde, brunette, etc.) or marital status (single, married, etc.) are qualitative data.

The median is the value separating the higher half from the lower half of a data sample. If the data set has an odd number of observations, the number in the middle is the median. If there is an even number of observations, the median is defined as the arithmetic mean of the two middle values.

If a confidence interval for a mean difference or an effect size includes zero, it suggests that there is no effect in the population and that the observed effect in the sample is likely due to sampling error.

The Law of Large Numbers has many practical applications. For example, insurance companies use it to predict future claim amounts. The law allows them to predict losses and to set premiums in a way that ensures profitability, by basing predictions on large aggregations of independent or nearly independent losses.

High leverage points are observations with extreme values on the predictor variables. They can have a disproportionate influence on the estimation of the regression coefficients, potentially leading to a less reliable model.

Multicollinearity can cause large changes in the estimated regression coefficients for small changes in the data. Hence, it makes the coefficients less reliable and interpretable.

The Wilcoxon Signed Rank Test uses the magnitudes of differences for ranking.

The probability of an event A, given that another event B has occurred, is called the conditional probability of A given B. It is denoted as P(A

The sum of the squared loadings for a factor (i.e., the column in the factor matrix) which represents the variance in all the variables accounted for by the factor is known as eigenvalue in factor analysis.

When the residuals exhibit a pattern or trend rather than a random scatter, it can be a sign of model misspecification, i.e., the model doesn't properly capture the relationship between the predictors and the outcome variable.