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.

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.

Bayes' Theorem is most commonly used when new evidence is used to update the probability of an event. It provides a way to revise existing predictions or theories (prior probabilities) in light of new data (the likelihood).

An interaction term in a regression model is used to represent the combined effect of two independent variables on the dependent variable. It captures situations where the effect of one variable on the dependent variable is different at different levels of another variable.

Factor analysis is a statistical method used to describe variability among observed, correlated variables in terms of a potentially lower number of unobserved variables called factors. Its primary purpose is to identify the underlying structure and relationships within a set of variables.

Inferential statistics is the branch of statistics that involves using a sample to draw conclusions about a population. It takes data from a sample and makes inferences about the larger population from which the sample was drawn. For example, inferential statistics might use data from a sample of women to infer something about the mean weight of all women.

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.

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.

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

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.

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.