Pt. I. Foundations of data analysis. 1. Model specification and applied research. 2. Modelling an average. 3. Outliers, skewness and data transformations -- Pt. II. Regression and data analysis. 4. Data analysis and simple regression. 5. Partial regression: interpreting multiple regression coefficients. 6. Model selection and misspecification in multiple regression -- Pt. III. Analysing cross-section data. 7. Dealing with heteroscedasticity. 8. Categories, counts and measurements. 9. Logit transformation, modelling and regression -- Pt. IV. Regression with time-series data. 10. Trends, spurious regressions and transformations to stationarity. 11. Misspecification and autocorrelation. 12. Cointegration and the error correction model -- Pt. V. Simultaneous equation models. 13. Misspecification bias from single equation estimation. 14. Estimating simultaneous equation models -- App. A. The data sets used in this book --App. B. Statistical tables.