860-0006-00L Applied Statistics and Policy Evaluation
| Semester | Herbstsemester 2017 |
| Dozierende | I. Günther, K. Harttgen |
| Periodizität | jährlich wiederkehrende Veranstaltung |
| Lehrsprache | Englisch |
| Kommentar | Number of participants limited to 20. Science, Technology, and Policy MAS and MSc as well as MAS in Development and Cooperation have priority. |
Lehrveranstaltungen
| Nummer | Titel | Umfang | Dozierende | ||||
|---|---|---|---|---|---|---|---|
| 860-0006-00 G | Applied Statistics and Policy Evaluation
 | 3 Std. |
| I. Günther, K. Harttgen |
Katalogdaten
| Kurzbeschreibung | This course introduces students to key statistical methods for analyzing social science data with a special emphasis on causal inference and policy evaluation. Students learn to choose appropriate analysis strategies for particular research questions and to perform statistical analyses with the statistical Software Stata. |
| Lernziel | Students - have a sound understanding of linear and logit regression - know strategies to test causal hypotheses using regression analysis and/or experimental methods - are able to formulate and implement a regression model for a particular policy question and a particular type of data - are able to critically interpret results of applied statistics, in particular, regarding causal inference - are able to critically read and assess published studies on policy evaluation - are able to use the statistical software STATA for data analysis |
| Inhalt | The topics covered in the first part of the course are a revision of basic statistics and linear and logit regression analysis. The second part of the course focuses on causal inference and introduces methods such as panel data analysis, difference-in-difference methods, instrumental variable estimation, regression discontinuity design, and randomized controlled trials used for policy evaluation. The course shows how the various methods differ in terms of the required identifying assumptions to infer causality as well as the data needs. Students will apply the methods from the lectures by solving weekly assignments using statistical software and data sets provided by the instructors. These data sets will cover topics at the interface of policy, technology and society. Solving the assignments contributes to the final grade with a weight of 30%. |
Leistungskontrolle
| Information zur Leistungskontrolle (gültig bis die Lerneinheit neu gelesen wird) | |
Leistungskontrolle als Semesterkurs | |
| ECTS Kreditpunkte | 3 KP |
| Prüfende | I. Günther, K. Harttgen |
| Form | benotete Semesterleistung |
| Prüfungssprache | Englisch |
| Repetition | Repetition nur nach erneuter Belegung der Lerneinheit möglich. |
Lernmaterialien
| Keine öffentlichen Lernmaterialien verfügbar. | |
| Es werden nur die öffentlichen Lernmaterialien aufgeführt. |
Gruppen
| Keine Informationen zu Gruppen vorhanden. |
Einschränkungen
| Allgemein |  : Für Fachstudierende und Hörer/-innen ist eine Spezialbewilligung der Dozierenden notwendig |
| Plätze | Maximal 20 |
| Vorrang | Die Belegung der Lerneinheit ist bis 04.09.2017 nur durch die primäre Zielgruppe möglich |
| Primäre Zielgruppe | Science, Technology and Policy MSc (860000)
MAS ETH in Entwicklung und Zusammenarbeit (865000) MAS ETH in Science, Technology and Policy (869000) |
| Warteliste | Bis 09.09.2017 |
