Incorporating nearly 200 graphs and numerous examples and exercises that employ real data from the social sciences, the book begins with a consideration of the role of statistical data analysis in social research. It then moves on to cover the following topics: graphical methods for examining and transforming data; linear least-squares regression; dummy-variables regression; analysis of variance; diagnostic methods for discovering whether a linear model fit to data adequately represents the data; extensions to linear least squares, including logit and probit models, time-series regression, nonlinear regression, robust regression and nonparametric regression; and empirical methods for assessing sampling variation, including the bootstrap and cross-validation.