2025 (Current Year) Faculty Courses Liberal arts and basic science courses Humanities and social science courses
Statistics C
- Academic unit or major
- Humanities and social science courses
- Instructor(s)
- Aguru Ishibashi
- Class Format
- Lecture
- Media-enhanced courses
- -
- Day of week/Period
(Classrooms) - Class
- -
- Course Code
- LAH.T301
- Number of credits
- 200
- Course offered
- 2025
- Offered quarter
- 4Q
- Syllabus updated
- Mar 19, 2025
- Language
- Japanese
Syllabus
Course overview and goals
This course provides an introduction to the fundamental quantitative analysis methods used in the social sciences. Specifically, students will learn how to use the statistical software R to perform cross table, variance analysis, correlation, and regression analysis (including linear and logistic regression). Additionally, students will develop the ability to interpret the results obtained through these methods. Through this course, students will acquire the essential statistical techniques necessary for analyzing quantitative survey data in the social sciences.
Course description and aims
By completing this course, students will acquire the following skills:
1) Application of quantitative analysis methods in the social sciences.
2) Conducting statistical analysis using R.
3) Interpretation and presentation of analytical results.
Keywords
Quantitative sociology, Statistics, R
Competencies
- Specialist skills
- Intercultural skills
- Communication skills
- Critical thinking skills
- Practical and/or problem-solving skills
Class flow
Computer exercise
Course schedule/Objectives
| Course schedule | Objectives | |
|---|---|---|
| Class 1 | Quantitative analysis in social sciences | Understand the nature of quantitative analysis in social sciences. |
| Class 2 | Descriptive statistics | Understand descriptive statistics and acquire analytical skills. |
| Class 3 | Estimation and test | Understand estimation and test, and acquire analytical skills. |
| Class 4 | Cross table | Understand cross table and acquire analytical skills. |
| Class 5 | Analysis of Variance | Understand Analysis of Variance and acquire analytical skills. |
| Class 6 | Correlation | Understand correlation and acquire analytical skills. |
| Class 7 | Regression: single and multiple regression analysis | Understand regression and acquire analytical skills. |
| Class 8 | Regression: dummy variable and interaction | Understand dummy variable and interaction in regression. |
| Class 9 | Logistic regression | Understand logistic regression and acquire analytical skills. |
| Class 10 | Ordered and multinomial logistic regression | Understand ordered and multinomial logistic regression and acquire analytical skills. |
| Class 11 | Tips for Oral presentation with statistics analysis | Prepare the oral presentation. |
| Class 12 | Presentation | Presentation |
| Class 13 | Presentation | Presentation |
| Class 14 | Presentation | Presentation |
Study advice (preparation and review)
To enhance effective learning, students are encouraged to spend approximately 100 minutes preparing for class and another 100 minutes reviewing class content afterwards (including assignments) for each class.
They should do so by referring to textbooks and other course material.
Textbook(s)
Kazuhiro Kezuka, 2022, Introduction to Statistics for Social Sciences, Kodansha. (In Japanese)
Reference books, course materials, etc.
Materials will be specified by the instructor.
Evaluation methods and criteria
Students' course scores are based on class reports 50% and the final presentation 50% (35% from teacher and 15% from other students).
Related courses
- LAH.T101 ： Statistics A
- LAH.T201 ： Statistics B
- LAH.S434 ： Essence of Humanities and Social Sciences38:Statistics
Prerequisites
Students require the basic knowledge of statistics.
Other
Should the number of applicants for this course exceed the limit, a lottery system will be used to determine which students are admitted. Be sure to attend the first class.