Course Instructor: Nan Zhang (Office hours by appointment)
Course Website: https://nanzhangresearch.github.io/Data_Analysis_Tutorial
Date and Time: Fridays from 13:45 - 15:15 in C-108 Methodenlabor
This tutorial course accompanies the lecture “Datenauswertung: Data Analysis for Political Scientists.” We will practice basic methods of data analysis using the statistical software package Stata.
Attendance and participation: Classtime will consist of a mixture of hands-on practice with Stata programming and group discussion / problem-solving. I’m also happy to answer any questions you have regarding the material covered in Sean’s lecture.
Active, in-class participation is central to your learning process. Of course, situations could arise where you need to miss class. As a courtesy, please let me know beforehand if you cannot attend a class session.
Optional homeworks: we will provide you with optional weekly homeworks where you will have the opportunity to practice each week’s concepts at your own pace. These are not graded (and you should not submit them), but they will help you to reinforce what we learn in class and thereby prepare for the final exam. We will also provide homework solutions.
Required Assignments: There will be three assessed assignments over the course of the semester. Each of these assignments will be graded as either a pass or a fail; you need to pass each assignment in order to pass the tutorial. There will be one opportunity to retake an assignment if the original assignment is not passed.
Assignment due dates are:
The assignments must be completed individually. You must make a written declaration that the work is wholly your own when submitting your answers. Anyone discovered to have colluded or plagiarised from others will be failed.
Session 1 (16 Feb): Organizational issues and introduction to Stata
Session 2 (23 Feb): Data manipulation; frequencies, measures of central tendency and dispersion
Session 3 (1 March): Graphs
Session 4 (8 March): T-tests, hypothesis testing, statistical significance
Session 5 (15 March): Measures of association for nominal variables
Session 6 (22 March): Measures of association for ordinal and interval variables
Guidelines for Assignment 2 handed out.
Link to Midterm Evaluation Survey.
Easter Break
Session 7 (12 April): Bivariate Regression
Session 8 (19 April): Multivariate Regression
Session 9 (26 April): Regression assumptions I
Session 10 (3 May): Regression assumptions II
Break for Ascension / Christi Himmelfahrt
Nan will hold (virtual) office hours during regular class time if you have questions
Session 11 (17 May): Regression with categorical independent variables
Session 12 (24 May): Logistic regression
Break for Corpus Christi / Fronleichnam
Nan will hold (virtual) office hours during regular class time if you have questions
Stata
Starter Manual. Useful if you are opening Stata for the
first time.
glossary.do.
A summary of commands we’ll cover over the semester that you can
download and annotate for yourselves.
Statalist Forum: https://www.statalist.org/forums/help.
Can be very useful for specific questions. You can either search for
existing posts or add your own question if you can’t find an answer.
Stata Guide: https://wlm.userweb.mwn.de/Stata/.
Short introductions to some frequently used commands.
Stata Cheatsheet: http://geocenter.github.io/StataTraining/portfolio/01_resource/.
A glossary that summarises some popular commands and their syntax.
Official Stata Youtube channel: https://www.youtube.com/user/statacorp.
Very helpful how-to guides on some simple as well as more complex
procedures.
Anywhere Maths: https://www.youtube.com/channel/UCRkeyHV2bANRrFjesu_wdLQ. Mostly useful for a recap of general mathematical questions and expressions. The playlist Statistical Measures might be particularly useful for you.