学部後期課程
学内のオンライン授業の情報漏洩防止のため，URLやアカウント、教室の記載は削除しております。
最終更新日：2024年4月22日
授業計画や教室は変更となる可能性があるため、必ずUTASで最新の情報を確認して下さい。
UTASにアクセスできない方は、担当教員または部局教務へお問い合わせ下さい。
最終更新日：2024年4月22日
授業計画や教室は変更となる可能性があるため、必ずUTASで最新の情報を確認して下さい。
UTASにアクセスできない方は、担当教員または部局教務へお問い合わせ下さい。
特殊講義「国際政治分析手法」
※The session in the first week will be held in a hybrid format (I will post the Zoom link to ITC-LMS)※
This course introduces students to basic skills for data management, analysis and visualization using R, a free and open source software. By the end of the course, students will be equipped with the foundation to conduct data analysis and effectively present their findings in the field of political science, as well as to critically assess scientific evidence shown in academic research, news reports, etc. that use statistical methods.
This course introduces students to basic skills for data management, analysis and visualization using R, a free and open source software. By the end of the course, students will be equipped with the foundation to conduct data analysis and effectively present their findings in the field of political science, as well as to critically assess scientific evidence shown in academic research, news reports, etc. that use statistical methods.
時間割／共通科目コード
コース名
教員
学期
時限
08C321688
FAS-CA4U17L1
特殊講義「国際政治分析手法」
吉本 郁
水曜5限
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
可
開講所属
教養学部
授業計画
Week 1. Guidance
Week 2. Introduction to R
- Installing R and R Studio
- Calculation, creation/manipulation of objects, and data loading using R
Week 3. Working with datasets available online
- Examples of online datasets
- Web-scraping using R
- Using APIs
*Assignment 1
Week 4. Data visualization
- Basic charts
- Using ggplot
Week 5. Geographic Data and TIme-Series Data
*Assignment 2*
Week 6. (May 25) Basic statistics and probability distributions (1)
- Random variables
- Probability distributions
- Discussing the final project
Week 7. Basic statistics and probability distributions (2)
- Sample and Population
- Law of Large Numbers and Central Limit Theorem
- Hypothesis testing
*Assignment 3
Week 8. Regression (1)
- Ordinary Least Squares
Week 9. Regression (2)
- Omitted variable bias
- Categorical variables: logit and probit regression
Week 10. Regression (3)
- Time-series and other topics
*Assignment 4
Week 11.
- Q&A and backup
Weeks 12-13.
Presentation of final projects
授業の方法
I upload lecture videos (the average length will be around 30 minutes) by the Friday of the week before each class session, which all participants are required to watch. I will use class sessions for reviewing lectures, answering questions about them, and having you work on exercises (a teaching assistant and I will help you when you encounter difficulties).
成績評価方法
Class participation: 20%
Bi-weekly assignments: 40%
Final project (presentation and final paper): 40%
教科書
Long, James D., and Paul Teetor. R Cookbook: Proven Recipes for Data Analysis, Statistics, and Graphics. 2nd Edition. O'Reilly Media, 2019. (The online version is available for free.)
Gelman, Andrew, and Jennifer Hill. Data analysis using regression and multilevel/hierarchical models. Cambridge University Press, 2006.
参考書
Imai, Kosuke (2018). Quantitative social science: An introduction. Princeton University Press.
履修上の注意
The focus of this course is on learning programing skills of R to do data management, visualization and analysis, so a mathematical background in probability and statistics is not a prerequisite, but students are strongly encouraged to complement this course with these fundamentals.
※The session in the first week will be held in a hybrid format (I will post the Zoom link to UTOL)※
その他
※The session in the first week will be held in a hybrid format (I will post the Zoom link to UTOL)※
