This book is a graduate-level econometrics text intended for first-year students. It covers basic econometric methods and their underlying assumptions, with a focus on estimation, hypothesis testing, and prediction. The first six chapters do not require matrix algebra and can be used in an advanced undergraduate course. The book includes empirical examples using various econometric software packages such as EViews, SAS, STATA, TSP, SHAZAM, Microfit, PcGive, LIMDEP, and GAUSS. It is not encyclopedic and does not cover Bayesian econometrics or nonparametric methods, which are considered more advanced topics. The book strikes a balance between a rigorous theoretical approach and an empirical approach. It includes exercises and empirical illustrations, with data sets from published articles. The book is not an applied econometrics text, and readers are encouraged to consult Berndt's textbook for an applied approach. The book references several classic econometrics texts and provides a list of references at the end of each chapter. The book is structured into parts, with Part I covering basic econometric concepts and Part II covering more advanced topics such as the general linear model, regression diagnostics, generalized least squares, seemingly unrelated regressions, simultaneous equations models, pooling time-series of cross-section data, limited dependent variables, and time-series analysis. The book is written for economists and econometricians and is intended to provide a solid foundation in econometric methods.This book is a graduate-level econometrics text intended for first-year students. It covers basic econometric methods and their underlying assumptions, with a focus on estimation, hypothesis testing, and prediction. The first six chapters do not require matrix algebra and can be used in an advanced undergraduate course. The book includes empirical examples using various econometric software packages such as EViews, SAS, STATA, TSP, SHAZAM, Microfit, PcGive, LIMDEP, and GAUSS. It is not encyclopedic and does not cover Bayesian econometrics or nonparametric methods, which are considered more advanced topics. The book strikes a balance between a rigorous theoretical approach and an empirical approach. It includes exercises and empirical illustrations, with data sets from published articles. The book is not an applied econometrics text, and readers are encouraged to consult Berndt's textbook for an applied approach. The book references several classic econometrics texts and provides a list of references at the end of each chapter. The book is structured into parts, with Part I covering basic econometric concepts and Part II covering more advanced topics such as the general linear model, regression diagnostics, generalized least squares, seemingly unrelated regressions, simultaneous equations models, pooling time-series of cross-section data, limited dependent variables, and time-series analysis. The book is written for economists and econometricians and is intended to provide a solid foundation in econometric methods.