This is a class in applied single equation regression analysis. It will be assumed that students have mastered the topics of basic statistics. Based on this assumption, we will examine regression analysis and its related techniques of quantitative analysis in two steps. The first topic is a review of the single equation OLS regression model in bivariate and multivariate applications. The emphasis would be developing an understanding of the logic of OLS regression, understanding of the parameter estimates they generate, and understanding the use of statistical tests to assess such models. The second topic will be a review of the assumptions underlying the OLS regression model. Each assumption – concerning specification, homoskedasticity, collinearity, and so on – will be identified and their implications for evaluating the OLS regression results discussed. We will then consider diagnostic tools to assess the presence and severity of violations of the OLS assumptions and – where possible – consider how they might be corrected. The emphasis throughout will be on the substantive interpretation of regression results.
Let op: De bijeenkomst van 30 november kan door omstandigheden niet doorgaan. U wordt verwacht bij de bijeenkomst van 6 november!*
- Dinsdag 06/11 t/m 11/12 van 11-13 uur in SC-01
NNB. De collegestof behoort ook tot de tentamenstof en/of opdrachten voor zover vastgelegd in sheets, handouts en andere informatiedragers.