860-0006-00L Essential Tools and Statistics for Impact and Policy Evaluation
| Semester | Herbstsemester 2018 |
| Dozierende | L. Beiser-McGrath |
| Periodizität | jährlich wiederkehrende Veranstaltung |
| Lehrsprache | Englisch |
| Kommentar | Number of participants limited to 20. Science, Technology, and Policy MSc and MAS students have priority. This lecture had been offered until autumn semester 2017 with the title "Applied Statistics and Policy Evaluation". Students who has completed that lecture cannot take credit points for this lecture again. |
| Kurzbeschreibung | This course aims to equip students with the basic knowledge and skills to both understand and conduct the evaluation of policies. This will involve both learning about statistical models and their appropriateness for estimating causal effects, as well as developing skills using statistical software to implement these models. |
| Lernziel | Students will: - know strategies to test causal hypotheses using regression analysis and/or experimental methods - be able to critically interpret results of applied statistics, in particular, regarding causal inference - be able to critically read and assess published studies on policy evaluation - learn to use the statistical software R |
| Inhalt | This course aims to equip students with the basic knowledge and skills to both understand and conduct the evaluation of policies. The first part of the course offers a thorough treatment of the classical linear regression model, the workhorse model for quantitative data analysis, and the program R that will be used for statistical analysis. The second part of the course focuses on more advanced methods that aim to estimate causal effects from observational data. |