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STATISTICS 1
| Subtitle | Descriptive Statistics, Statistical Inference, and Hypothesis Testing |
|---|---|
| Lecturer(s) | AKABAYASHI, YOSHIO |
| Credit(s) | 2 |
| Academic Year/Semester | 2024 Spring |
| Day/Period | Mon.4 |
| Campus | Hiyoshi |
| Class Format | Face-to-face classes (conducted mainly in-person) |
| Registration Number | 37659 |
| Faculty/Graduate School | ECONOMICS |
| Department/Major | ECONOMICS Type A, B |
| Year Level | 1 |
| Class Specification | 23, 24, 25, 26, 36, 37 |
| Field | FOUNDATION MANDATORY (1ST YEAR) |
| Grade Type | This item will appear when you log in (Keio ID required). |
| Course Description | Lectures on the basics of theoretical and empirical methods of statistics, which are often used in economic analysis. Learn the basics of statistical description, statistical inference, and probability theory to understand the structure of a population from a sample. In the class, while giving familiar concrete examples, we will touch on how statistics are used and practice data processing. |
| K-Number | FEC-EC-13101-211-60 |
| Course Administrator | Faculty/Graduate School | FEC | ECONOMICS |
|---|---|---|---|
| Department/Major | EC | ECONOMICS | |
| Main Course Number | Level | 1 | First-year level coursework |
| Major Classification | 3 | Foudation Course / Major Subjects Course - Introductory Subject | |
| Minor Classification | 10 | Foundational Course - Statistics | |
| Subject Type | 1 | Required subject | |
| Supplemental Course Information | Class Classification | 2 | Lecture |
| Class Format | 1 | Face-to-face classes (conducted mainly in-person) | |
| Language of Instruction | 1 | Japanese | |
| Academic Discipline | 60 | Information science, computer engineering, and related fields | |
Course Contents/Objectives/Teaching Method/Intended Learning Outcome
The main purpose of the lecture is to make it possible to acquire the basic ability of statistical analysis by learning the following contents.
(1) Statistical description (how to capture characteristics of data)
(2) Statistical estimation (how to estimate characteristics of population distribution from sample)
(3) Statistical testing (how to test theoretical claims)
Not only lectures but also exercises will be emphasized, and also statistical processing using computers will be instructed.
(1) Statistical description (how to capture characteristics of data)
(2) Statistical estimation (how to estimate characteristics of population distribution from sample)
(3) Statistical testing (how to test theoretical claims)
Not only lectures but also exercises will be emphasized, and also statistical processing using computers will be instructed.
Active Learning MethodsDescription
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Preparatory Study
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Textbooks
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