2024 Faculty Courses Liberal arts and basic science courses Humanities and social science courses
Statistics B
- Academic unit or major
- Humanities and social science courses
- Instructor(s)
- Shin Okubo
- Class Format
- Lecture (Face-to-face)
- Media-enhanced courses
- -
- Day of week/Period
(Classrooms) - Intensive
- Class
- -
- Course Code
- LAH.T201
- Number of credits
- 200
- Course offered
- 2024
- Offered quarter
- 2Q
- Syllabus updated
- Mar 17, 2025
- Language
- Japanese
Syllabus
Course overview and goals
This course examines descriptive statistics and inferential statistics, both are indispensable to the analysis of social survey data. Descriptive statistics summarize the characteristics of a sample, and inferential statistics generalize the characteristics of the population from a sample.
Students not only learn the basics of them, but apply them to analyze social survey data and discuss the results using practical approaches. This leads students to consider how to think about various issues in contemporary society (e.g. economic inequality, meritocracy, health, declining birthrate and aging population, time use, gender).
This course treats social gap and inequality as the main topic of analysis, using some large-scale social survey data.
Course description and aims
At the end of this course, students will be able to:
1) Understand the basic process of social surveys.
2) Learn basic methods of analysis of social survey data.
3) Adequately describe and explain social phenomena using analytic findings.
Keywords
social statistics, descriptive statistics, inferential statistics, probability, estimate, hypothesis test, analysis of variance (ANOVA), correlation, regression
Competencies
- Specialist skills
- Intercultural skills
- Communication skills
- Critical thinking skills
- Practical and/or problem-solving skills
Class flow
Using the handouts, the instructor will lecture on basic methods of statistics for social data analysis and practical analyses of survey data. After last class, the take-home test (including a review test and a short report) must be submitted by the due date.
This course is an intensive course. The schedule is as follows.
Thursday, 22nd Aug 2024: Class 1 (period 3-4), Class 2 (period 5-6), Class 3 (period 7-8)
Friday, 23rd Aug 2024: Class 4 (period 3-4), Class 5 (period 5-6), Class 6 (period 7-8)
Tuesday, 27th Aug 2024: Class 7 (period 3-4), Class 8 (period 5-6), Class 9 (period 7-8)
Wednesday, 28th Aug 2024: Class 10 (period 5-6), Class 11 (period 7-8)
Thursday, 29th Aug 2024: Class 12 (period 3-4), Class 13 (period 5-6), Class 14 (period 7-8)
Information on the lecture room will be provided as soon as decided.
Course schedule/Objectives
| Course schedule | Objectives | |
|---|---|---|
| Class 1 | Introduction: outline of statistics for social data analysis, the rudiments of social research methods | Understand the function of social statistics and data collection method. |
| Class 2 | Descriptive statistics: frequency distribution and graphing, central tendency, variation | Understand the importance of descriptive statistics and how to summarize data. |
| Class 3 | Basic concept of inferential statistics: population and sample, estimate, hypothesis test | Understand the importance of inferential statistics, the relationship between central limit theorem and estimate, and hypothesis test. |
| Class 4 | Probabitily distribution [1]: binominal distribution | Understand the theory of binominal distribution. |
| Class 5 | Probabitily distribution [2]: normal distribution | Understand the theory of normal distribution. |
| Class 6 | Estimate for population mean and population proportion | Understand point estimate and interval estimate. |
| Class 7 | Mean difference test and significance testing with proportions | Understand mean difference test and significance testing with proportions. |
| Class 8 | Crosstabulation and chi-square test | Understand how to examine the relationship between two qualitative variables. |
| Class 9 | One-way analysis of variance | Understand one-way analysis of variance. |
| Class 10 | Two-way analysis of variance | Understand two-way analysis of variance. |
| Class 11 | Correlation and regression, OLS (ordinary least squares) | Understand correlation coefficient and linear regression. |
| Class 12 | Regression Analysis | Understand multiple regression analysis and binominal logistic regression analysis. |
| Class 13 | The main point of how to read research articles [1]: research question and methods | Read research articles using social statistics and explain the relationship between research question and methods. |
| Class 14 | The main point of how to read research articles [2]: results and discussion | Read research articles using social statistics and explain the relationship between results and discussion. |
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)
None required. (Note: Handouts based on several reference books are distributed in PDF format.)
Reference books, course materials, etc.
Bohrnstedt, G. W. and D. Knoke, 1988, Statistics for Social Data Analysis, 2nd ed., F. E. Peacock Publisher; ISBN-13: 978-0875813233
Kezuka, K., 2022, Introduction to Statistics for Social Sciences, Kodansha.(In Japanese); ISBN-13: 978-4065284506
Evaluation methods and criteria
Grades are based on class participation (10%) and a take-home test includes the following.
[1] Review test of the course content (70%)
[2] Short report on the results of specific analysis of different issues in contemporary society (20%)
Related courses
- LAH.T101 ： Statistics A
- LAH.T301 ： Statistics C
- LAH.S434 ： Essence of Humanities and Social Sciences38:Statistics
Prerequisites
Nothing in particular.
Other
This is an intensive lecture. As a general rule, the authorized absence system does not apply to intensive lecture-style courses.
If acquiring credits for this course is related to your own graduation, eligibility for undergraduate major affiliation or for independent research project for the Bachelor's Degree, please fully understand the risks before taking this course.