This document discusses correlation, regression, and the least squares method. It defines correlation as the degree of relationship between two variables and identifies positive, negative, and zero correlations. Regression analysis determines the best fit line to predict the relationship between a dependent and independent variable. Linear regression predicts the relationship between quantitative variables, while logistic regression predicts probabilities for discrete outcomes. The least squares method determines the best fit line by minimizing the distance between the data points and the line. Real-life examples are provided to illustrate applications in business, agriculture, medicine, and investments.