English

年度	2024年度	開講部局	人間社会科学研究科博士課程前期人文社会科学専攻国際経済開発プログラム
講義コード	WMH00002	科目区分	専門的教育科目
授業科目名	Quantitative and Analytical Social Science
授業科目名 （フリガナ）	シャカイカガクノタメノスウリ・ケイリョウブンセキ
英文授業科目名	Quantitative and Analytical Social Science
担当教員名	西條　春信
担当教員名 (フリガナ)	サイジョウ　ハルノブ
開講キャンパス	東広島	開設期	1年次生   後期   ３ターム
曜日・時限・講義室	(3T) 火1-4：国際203号
授業の方法	講義	授業の方法 【詳細情報】
			講義中心、演習中心、板書多用、ディスカッション、学生の発表、野外実習、作業、薬品使用
単位	2.0	週時間		使用言語	E : 英語
学習の段階	5 : 大学院基礎的レベル
学問分野（分野）	24 : 社会科学
学問分野（分科）	02 : 政治学
対象学生
授業のキーワード	causal inference, statistics, data analysis, research design
教職専門科目		教科専門科目
プログラムの中での この授業科目の位置づけ （学部生対象科目のみ）
到達度評価 の評価項目 （学部生対象科目のみ）
授業の目標・概要等	Students are expected to learn the basic concepts and skills for making quantitative causal inferences for the social sciences, implementing these methods on R, and successfully writing and presenting a quantitative research proposal with a research design.
授業計画	lesson1 Introduction to Data Analysis lesson2 Exercises - Introduction to R and RStudio lesson3 Causality with Randomized Experiments lesson4 Exercises - Analyzing and Interpreting Experiments lesson5 Survey Research lesson6 Exercises - Survey Design and Analysis lesson7 Student Presentations lesson8 Student Presentations lesson9 Linear Regressions lesson10 Exercises - Linear Regressions lesson11 Causal Inference with Observational Data lesson12 Exercises - Causal Analysis with Observational Data lesson13 Uncertainty and Probability lesson14 Exercises - Estimating and Interpreting Uncertainty lesson15 Student Presentations Students will submit and present a research paper or a research proposal that incorporates some of the quantitative methods presented in the class. This will provide an opportunity to develop the quantitative portions of students' thesis research or other research projects. Students are required to come to office hours in the first half of the quarter to discuss their topics and interests, and submit a short proposal or outline by the fifth week.
教科書・参考書等	Llaudet, Elena, and Kosuke Imai. Data analysis for social science: a friendly and practical introduction. Princeton University Press, 2022.
授業で使用する メディア・機器等
	【詳細情報】
授業で取り入れる 学習手法
予習・復習への アドバイス	This course has no prerequisites, though basic arithmetic and probability will be helpful. Prior knowledge of data science, statistics, and experiments will also be helpful but not required. This course is intended for first-year masters students without strong quantitative methodological backgrounds, and will cover the basic concepts and implementation for causal inference techniques. PLEASE TRY TO INSTALL: R and RStudio prior to the first class, so that the introductory part can proceed smoothly. Students are asked to read the relevant chapters prior to the lectures, so that they can get the most use out of them. This class would be more helpful for those who are looking to design and implement a research project that involves quantitative analysis. PLEASE obtain Data Analysis for Social Science: A Friendly and Practical Introduction by Elena Llaudet and Kosuke Imai as a paper or electronic copy from the usual places before class. This class is intended to introduce students to research design in the social sciences, especially those that incorporate causal inference. This course will also introduce students to basic data analysis using R, so that students can learn to implement the tools introduced in lectures during exercises so that they can apply them to their own research or other practical uses. Students will be asked to submit short proposals for their research proposals or papers during the middle of the semester, and they will present their research at the end of the semester so that they can obtain feedback from the instructor and/or their peers.
履修上の注意 受講条件等
成績評価の基準等	(1) Class participation (20%) (2) First research proposal and in-class presentation (20%) (3) Take-home quizzes (20%) (4) Final research proposal and in-class presentation (40%) The research proposals will be 2-3 pages in English. The initial proposal should present a coherent research question, a literature review, and a tentative research design for a topic in the social sciences (economics, political science, sociology, etc). The student will revise the proposal to submit as the final 3-5 page research proposal/presentation with a concrete research design. Specific deadlines and grading criteria will be announced 2-4 weeks before the deadlines.
実務経験
実務経験の概要と それに基づく授業内容
メッセージ
その他	Class schedule and requirements are subject to change.
すべての授業科目において，授業改善アンケートを実施していますので，回答に協力してください。 回答に対しては教員からコメントを入力しており，今後の改善につなげていきます。