京都大学 京都大学

Statistical data analysis, Basic A

Numbering Code G-ECON31 6A612 LJ44
G-ECON31 6A612 LJ43
G-ECON31 6A612 LJ10 		Year/Term 2022 ・ First semester
Number of Credits 2 Course Type Lecture
Target Year Target Student
Language Japanese Day/Period Mon.2
Instructor name AKITA YUYA (Graduate School of Economics Professor)
Outline and Purpose of the Course Analyzing various data to extract meaningful and valuable information, and constructing models to represent and interpret data, are important techniques these days. Data is becoming bigger and bigger, thus efficient and effective ways of data processing are required. In this course, we will learn basic methods for statistical analysis of data, and exercise them by using the Python language.
Note that "Statistical Data Analysis, Basic B" has the same content while it uses a different language, therefore students may not take both.
Course Goals - Understanding the fundamentals of data analysis and basic methods.
- Learning processes of the methods in the Python language.
Schedule and Contents Generally, two or three lectures, including exercises with Python, will be conducted on each of the following topics. Depending on the progress of the class, the order of topics and the number of lectures may be changed, or some part may be omitted.

Basics of data analysis (representation of data, preprocessing, databases, etc.)
Basics of the Python language
Basics of statistics (statistics, estimation, test, etc.)
Analysis of multivariable data (regression analysis, etc.)
Other topics
Evaluation Methods and Policy Evaluation will be based on midterm and end-term reports (50 marks each).
Course Requirements Basic understanding of statistics. Although programming skills are not required, basic knowledge and skills to use computers are expected.
Study outside of Class (preparation and review) Each class requires understanding of the contents of the previous lectures, thus review them thoroughly.
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