学部・大学院区分
Undergraduate / Graduate
経済学部
時間割コード
Registration Code
0411553
科目区分
Course Category
科目名 【日本語】
Course Title
社会科学の分析と方法Ⅰ(E)
科目名 【英語】
Course Title
Specialized Advanced Lecture(Social Science Analysis and Methods I)(E)
コースナンバリングコード
Course Numbering Code
担当教員 【日本語】
Instructor
GREEN David James ○
担当教員 【英語】
Instructor
GREEN David James ○
担当教員所属【日本語】
instructor's belongs
担当教員所属【英語】
instructor's belongs
単位数
Credits
2
配当年次
dividend Yearly
開講期・開講時間帯
Term / Day / Period
秋 火曜日 1時限
Fall Tue 1
授業形態
Course style
講義
Lecture


授業の目的 【日本語】
Goals of the Course(JPN)
授業の目的 【英語】
Goals of the Course
This course teaches the use of social science quantitative techniques, emphasizing applications of value to administrators and researchers alike in the fields of law, political science, public policy, and public and international affairs. It includes a review of theoretical application as well as practical use of descriptive statistics and an introduction to hypothesis testing.
到達目標 【日本語】
Objectives of the Course(JPN)
Quantitative Analysis is designed to provide students with the knowledge and skills to reach a new level of understanding and analysis of social science data. The course will begin broadly by teaching students how to develop good, quantifiable research questions and what the best methods are to answer them. Students will learn to use statistics as a method of determining what, if any relationships exist between variables and if those relationships are significant. By the end of the term, students should have the tools not only to develop and test their own research questions but also to read and critique the work of other authors in books and scholarly journals with an eye towards finding areas of the discipline that are in need of future research.
授業の内容や構成
Course Content / Plan
Lecture 1 - Course intro & guidance
Lecture 2 - Key concepts, using statistics in the research process, levels of measurement
Lecture 3 - Basic descriptive statistics, displaying data
Lecture 4 - Measures of central tendency
Lecture 5 - Measures of dispersion
Lecture 6 - Review for midterm exam
Lecture 7 - Midterm exam
Lecture 8 - Measures of dispersion (cont.), the normal curve
Lecture 9 - z-scores, area under the curve
Lecture 10 - Inferential statistics, sampling distribution, central limit theorem
Lecture 11 - Bias and efficiency, confidence
Lecture 12 - Hypothesis testing
Lecture 13 - Two-tailed t-tests
Lecture 14 - Significance testing
Lecture 15 - Review for final exam
履修条件・関連する科目
Course Prerequisites and Related Courses
No prerequisites are required for this course. A mathematical background is not expected, but students should know basic algebra at a minimum
成績評価の方法と基準
Course Evaluation Method and Criteria
10% Class Participation/Attendance
20% Written Assignments
35% Midterm Exam
35% Final Exam
教科書・参考書
Textbook/Reference Book
Healey, Joseph F. The Essentials of Statistics: A Tool for Social Science Research. 2nd ed. Wadsworth, 2011.
課外学習等(授業時間外学習の指示)
Study Load(Self-directed Learning Outside Course Hours)
Please read the assigned readings in preparation for each class.
注意事項
Notice for Students
授業開講形態等
Lecture format, etc.
教育レベルが1以下の場合、原則として対⾯授業とする。ただし、対⾯授業を希望しない学生には遠隔(同時双⽅向型またはオンデマンド型)でも受講できるよう、「対面・遠隔(同時双⽅向型またはオンデマンド型)の併⽤」とする。遠隔はNUCT等で行う。なお、オンデマンド型の場合、教員への質問および授業に関する受講学⽣間の意⾒交換は、NUCT機能「メッセージ」により⾏うこと。
※履修登録後(本通知以後)に授業形態等に変更がある場合には、NUCTの授業サイトで案内します。
遠隔授業(オンデマンド型)で行う場合の追加措置
Additional measures for remote class (on-demand class)