Statistical data analysis, Basic B
| Numbering Code |
G-ECON31 6A616 LJ43 G-ECON31 6A616 LJ10 G-ECON31 6A616 LJ44 |
Year/Term | 2022 ・ First semester | |
|---|---|---|---|---|
| Number of Credits | 2 | Course Type | Lecture | |
| Target Year | Target Student | |||
| Language | Japanese | Day/Period | Thu.1・2 | |
| Instructor name | MATSUI HIROYUKI (Graduate School of Management Professor) | |||
| Outline and Purpose of the Course |
Arranging and analyzing various data to extract meaningful and valuable information, and constructing models for expressing and interpreting data, is important technology in the modern day. Data is growing yearly, and it is necessary to perform these processes efficiently and effectively by appropriate means. In this lecture, we will learn basic methods for statistically analyzing data and practice using the Python language. Note that "Basic Statistical Data Analysis A" has the same content and uses only a different language, so students may not take both. In particular, note that dealing with pattern learning and machine learning and developing content requires the Python language, which is taught in 'Statistical Data Analysis Application A'. |
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| Schedule and Contents |
Generally, two or three lectures will be conducted on each of the following topics and practiced using the R language. The order and number of themes will be changed accordingly depending on class progress. Basics of data analysis (representation of data, preprocessing, databases, etc.) Basics of the R language Basics of statistics (statistics, estimation, test, etc.) Analysis of multivariable data (regression analysis, etc.) Bayesian statistics |
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| Evaluation Methods and Policy | Evaluation will be based on midterm and end-term reports (50 marks each). Students absent for more than one third of the course will not be given credits. | |||
| Course Requirements | Basic understanding of statistics. Although programming knowledge is not required, basic knowledge and operation of computers is expected. | |||
| Study outside of Class (preparation and review) | Each class assumes an understanding of the contents of the previous lectures, so please review thoroughly. | |||
| Textbooks | Textbooks/References | Not determined | ||
| References, etc. | Introduced during class | |||
