Keio University Syllabus and Timetable

STATISTICS 2

SubtitleRegression Analysis, Application of Statistical Analysis in Social Science, and Mathematical Basis of Statistics
Lecturer(s)AKABAYASHI, YOSHIO
Credit(s)2
Academic Year/Semester2024 Fall
Day/PeriodMon.4
CampusHiyoshi
Class FormatFace-to-face classes (conducted mainly in-person)
Registration Number26137
Faculty/Graduate SchoolECONOMICS
Department/MajorECONOMICS Type A, B
Year Level1
Class Specification23, 24, 25, 26, 36, 37
FieldFOUNDATION MANDATORY (1ST YEAR)
Grade TypeThis item will appear when you log in (Keio ID required).
Course DescriptionLectures 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 AdministratorFaculty/Graduate SchoolFECECONOMICS
Department/MajorECECONOMICS
Main Course NumberLevel1First-year level coursework
Major Classification3Foudation Course / Major Subjects Course - Introductory Subject
Minor Classification10Foundational Course - Statistics
Subject Type1Required subject
Supplemental Course InformationClass Classification2Lecture
Class Format1Face-to-face classes (conducted mainly in-person)
Language of Instruction1Japanese
Academic Discipline60Information science, computer engineering, and related fields

Course Contents/Objectives/Teaching Method/Intended Learning Outcome

(1) By learning the regression analysis (analysis on causality between multiple variables), students will learn about the basics of empirical analysis of economic theory.
(2) By learning the applied statistical analysis (statistical analysis about various economic and social phenomena), students will develop the ability to apply statistics to a wide range in the real world.
(3) By learning the mathematical basis of statistics, students will be able to prepare for more advanced statistical analysis.
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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Course Plan

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Method of Evaluation

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Textbooks

Textbooks will be announced at the Session 1.

Reference Books

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Lecturer's Comments to Students

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