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Course Detail

Degree
Bachelor
Standard Academic Year
1・2
Course delivery methods
Hybrid or Others
Subject
Social studies, Languages
Program
School
School of Social and International Studies
Department
Campus
Tsukuba Campus
Classroom
Course Offering Year
2022-2023
Course Offering Month
October - December
Weekday and Period
Tue3,4
Capacity
Credits
2.0
Language
English
Course Number
BE21831

Quantitative Methods for Social Sciences University of Tsukuba

Course Overview

This course introduces students to the fundamental of causal inference that constitutes the core of quantitative social sciences today. The course is divided into three parts: (1) conceptual discussion of causal inference, (2) elementary statistical theory, and (3) programming with statistical software. We are using a free software, R, which has been widely used by both scientists and major multinational corporations including Google.

Learning Achievement

This course places emphasis on the importance of research design that comes before any application of statistical model. In other words, one of the most important objectives of this course is that students realize difficulties and challenges associated with causal inference. After this course, interested students are encouraged to take courses on statistics (e.g., BE22321) and econometrics (e.g., BE22231) to further learn different statistical techniques that are available today.

Competence

In this course, lectures proceed with data analyses examples with R. Students are expected to actively practice data analyses during the lectures in order to improve their programming skills, learn how to conduct quantitative research, and better understand causal inference. Data analyses examples are drawn from different fields of social sciences including political science, economics, and public policy. Quizzes, programing assignments, and problem sets are used to assess how well students are understanding materials covered in this course.

Course prerequisites

No course is required.

Grading Philosophy

Course grades will be based on:
- Active reading of the course textbook through Perusall (20%)
- Programming assignments (10%)
- Problem sets (30%)
- Two take-home exams (20% each)
- No extra/optional credit assignments will be offered to individual students.

Course schedule

Course type

Lectures

Online Course Requirement

Instructor

Seki Katsunori

Other information

Students learn course materials through video lectures. They also attend live computer lab sessions that are held online during a part of the class time.
Lecture is conducted in English.
G-course. Hybrid or Others
The number of students is limited to 20. Priorities are given to students from the College of Social Sciences and the College of International Studies. Class Attendance
Although attendance does not factor explicitly in your grade, to do well in this course it is important that you come to class regularly. Most importantly, if you miss class meetings more than three times (i.e., four times or more), your grade becomes D (Fail) regardless of your performance. This is a university rule that I will follow strictly, and therefore I will take attendance at the beginning of each class.

Site for Inquiry

Please inquire about the courses at the address below.

Contact person: Katsunori Seki


Link to the syllabus provided by the university