The goal of the book is to facilitate both teaching of applied econometrics, particularly in undergraduate and Master courses, and learning by students and, more generally, by those concerned with a formal measurement of economic events. Statistics is needed for a correct formulation of the problem and interpretation of the results, but an excess of formalization may discourage students. For this reason, the statistical content of this book is rigorous but limited to what is strictly necessary for a proper application of the methods. All theoretical concepts are then illustrated empirically, with examples that use either simulated data, in order to have a more immediate and controlled feedback, or actual data on economic variables. The software used is EViews, usually available in academic computer rooms or otherwise at an affordable price. Chapter 1 contains a brief introduction to the problems faced by econometrics and to different types of economic (or, more generally, social) data that can be analyzed with econometric techniques. Chapter 2 presents the linear regression model, which often provides a good representation of the relationships between economic variables, and the estimators of the parameters of the model and their properties. Chapter 3 focuses on techniques to test hypotheses about the parameters of the linear regression model. Chapter 4 assesses the effects of violations of the assumptions underlying the linear model and develops extended versions of the model that require less restrictive conditions of applicability. Chapter 5 examines the consequences of unmodelled changes in the model parameters and possible remedies. Chapter 6 explicitly considers the case of stochastic explanatory variables. Chapter 7 proposes an introduction to dynamic models. Chapter 8 discusses models for panel data, which have both a longitudinal and a temporal dimension. Chapter 9 deals with models for binary variables, such as those resulting from questionnaires or other types of qualitative analyses. Each chapter begins with the necessary theoretical background, continues with the practical applications based on simulated and real data using EViews, and concludes with a summary of the main concepts developed in the chapter and with both theoretical and applied exercises as a way to test and improve learning.