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最終更新日:2024年3月15日

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Quantitative Social Science

Quantitative Social Science: An Introduction
Would universal health insurance improve the health of the poor? Do patterns of arrests in US cities show evidence of racial profiling? What accounts for who votes and their choice of candidates? This course will teach students how to address these and other social science questions by analyzing quantitative data. The course introduces basic principles of statistical inference and programming skills for data analysis. The goal is to provide students with the foundation necessary to analyze data in their own research and to become critical consumers of statistical claims made in the news media, in policy reports, and in academic research.
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時間割/共通科目コード
コース名
教員
学期
時限
25-304-12
GLP-LP6301L3
Quantitative Social Science
今井 耕介
S1 S2
集中
マイリストに追加
マイリストから削除
講義使用言語
英語
単位
2
実務経験のある教員による授業科目
NO
他学部履修
開講所属
法学政治学研究科
授業計画
The class will cover the following topics based on the assigned textbook: 1. Causality 2. Measurement 3. Prediction 4. Probability 5. Uncertainty We will use R statistical programming language and analyze a variety of data sets used in published social science research.
授業の方法
The entire class will be taught in English.
成績評価方法
Problem sets, Participation, Take-home final exam
教科書
Kosuke Imai (2017). Quantitative Social Science: An Introduction. Princeton University Press
参考書
None
履修上の注意
If you decide to enroll, please fill in the form at http://bit.ly/***** Any questions about the course should be directed to the teaching fellow, Saki Kuzushima *****
その他
There is no pre-requisite for this course. It is designed for those who are interested in learning how data analyses are used to analyze social science questions. The course will be taught in the same way as done at American universities. As such, active participation is essential for students to succeed in this course.