2021 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)
- Kazuhiro Kezuka
- Class Format
- Lecture
- Media-enhanced courses
- -
- Day of week/Period
(Classrooms) - 1-2 Mon (S011) / 1-2 Thu (S011)
- Class
- -
- Course Code
- LAH.T201
- Number of credits
- 200
- Course offered
- 2021
- Offered quarter
- 2Q
- Syllabus updated
- Jul 10, 2025
- Language
- Japanese
Syllabus
Course overview and goals
Inferential statistics is the tool to grasp the information of population using the survey data. This tool is essential for analysis of social surveys and big data. Students learn inferential statistics with topics of social sciences, especially social inequality.
Course description and aims
At the end of this course, students will be able to:
1) understand and utilize the concept of test and estimation,
2) build probability models of social statistics or events.
Keywords
descriptive statistics, inferential statistics, probability distribution, sampling, estimation, hypothesis testing, regression analysis
Competencies
- Specialist skills
- Intercultural skills
- Communication skills
- Critical thinking skills
- Practical and/or problem-solving skills
Class flow
The instructor will lecture about inference statistics based on the textbook. Students should solve some problems and submit their answers at the end of each class. At the end of term, students must take the final exam.
Course schedule/Objectives
| Course schedule | Objectives | |
|---|---|---|
| Class 1 | Introduction and Descriptive statistics |
Understand descriptive statistics and the importance of estimation and test. |
| Class 2 | Gini coefficient |
Understand how to grasp the inequality. |
| Class 3 | Mobility table |
Understand how to grasp the maintain of intergenerational inequality. |
| Class 4 | Standard error and random sampling |
Understand the relationship between standard error and random sampling. |
| Class 5 | Binomial distribution |
Understand binomial distribution and how to build probability model. |
| Class 6 | Normal distribution |
Understand normal distribution and Central Limit Theorem. |
| Class 7 | Point estimation and interval estimation |
Understand the logic of estimation. |
| Class 8 | Unbiased estimator |
Understand unbiased estimator. |
| Class 9 | Statistical test |
Understand the logic of test. |
| Class 10 | Testing the difference of means |
Understand how to test the difference of means. |
| Class 11 | Chi-squared test |
Understand Chi-squared test for cross table. |
| Class 12 | Analysis of variance |
Understand analysis of variance. |
| Class 13 | Test of correlation and t test |
Understand test of correlation and t test. |
| Class 14 | Regression analysis |
Understand regression analysis |
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)
Textbooks will be specified by the instructor.
Reference books, course materials, etc.
Textbooks will be specified by the instructor.
Evaluation methods and criteria
Students’ course scores are based on class reports 30% and the final report 70%.
Related courses
- LAH.T101 ： Statistics A
- LAH.T301 ： Statistics C
- LAH.S434 ： Essence of Humanities and Social Sciences38:Statistics
Prerequisites
No prerequisites.
Contact information (e-mail and phone) Notice : Please replace from ”[at]” to ”@”(half-width character).
kkezuka[at]ila.titech.ac.jp