This document discusses regression analysis techniques for predicting lawyer hourly rates. It provides an example regression model that estimates rate based on city, firm size, years of experience, practice area, and other independent variables. Graphs and equations are shown to illustrate how regression can be used to model the relationship between a dependent variable (rate) and multiple independent predictors. The document also discusses key regression concepts like the regression coefficient, standard error, and interpreting statistical significance.