Data analysis is quickly changing the way we understand and engage in politics, how we implement policy, and how organizations across the world make decisions. In this course, we will learn the fundamental principles of statistical inference and develop the necessary programming skills to answer a wide range of political and policy oriented questions with data analysis. Who is most likely to win the upcoming presidential election? Do countries become less democratic when leaders are assassinated? Is there racial discrimination in the labor market? These are just a few of the questions we will work on in the course.
Students are not expected to have any prior programming knowledge or experience. The course will be centered around bite-size assignments that will help build coding and statistical skills from scratch. Students will leave the course equipped for work in any setting that requires a social scientific approach to data analysis, from policy non-profits to government, from Silicon Valley to Wall Street and beyond. Syllabus: gvt201a_spring2017.pdf Textbook: Imai, Kosuke. Quantitative Social Science: An Introduction. Princeton University Press Lecture Notes- Lecture 1: Course Introduction
- Lecture 2: In-Class Exercise: Introduction to R
- Lecture 3: Causation
- Lecture 4: Causation and Descriptive Statistics of Single Variables
- Lecture 5: In-Class Exercise: Is There Racial Discrimination in the Labor Market?
- Lecture 6: Survey Data and Relating Variables to Each Other
- Lecture 7: In-Class Exercise: Do Political Leaders Make a Difference?
- Lecture 8: Prediction: Using Polls to Predict Elections
- Lecture 9: Prediction and Bivariate Regression Analysis: Using Appearance to Predict Elections
- Lecture 10: Prediction and Bivariate Regression Analysis: Using Population to Predict Service Requests in Boston
- Lecture 11: In-Class Exercise: Using 1996 to Predict 2000 Election Results
- Lecture 12: Causation and Bivariate Regression Analysis: Do Women Promote Different Policies?
- Lecture 13: Midterm Review
- Midterm
- Lecture 15: Prediction and Multivariate Regression Analysis: Using Population and Income to Predict Service Requests in Boston
- Lecture 16: Causation and Multivariate Regression Analysis: Does Social Pressure Affect Turnout?
- Lecture 17: After Spring Break Review
- Lecture 18: Probability Theory: Probability, Random Variables and Distributions
- Lecture 19: Probability Theory: Central Limit Theorem and Law of Large Numbers
- Lecture 20: Hypothesis Testing of Diffs-in-Means
- Lecture 21: In-Class Exercise: Does Social Pressure Affect Turnout?
- Lecture 22: In-Class Discussion of Proposed Experiments
- Lecture 23: Hypothesis Testing of Coefficients: Do Women Promote Different Policies?
- Lecture 24: In-Class Exercise: Does Social Pressure Affect Turnout?
- Lecture 25: In-Class Exercise: Does Listening to Classical Music Improve Productivity?
- Lecture 26: In-Class Exercise: Do Political Leaders Make a Difference?
- Lecture 27: Final Review