PROBABILITY[DS1]

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Lecturer(s)	SAKAI, SHOTARO
Credit(s)	2
Academic Year/Semester	2025 Spring
Day/Period	Mon.1
Campus	SFC
Class Format	Face-to-face classes (conducted mainly in-person)
Registration Number	41908
Faculty/Graduate School	POLICY MANAGEMENT / ENVIRONMENT AND INFORMATION STUDIES
Year Level	1, 2, 3, 4
Field	FUNDAMENTAL SUBJECTS SUBJECTS OF DATA SCIENCE DATA SCIENCE 1
Grade Type	This item will appear when you log in (Keio ID required).
Related Classes	B3101 統計基礎/INTRODUCTION TO STATISTICS B3103 微分・積分/CALCULUS B3104 線形代数/LINEAT ALGEBRA
Location	SFC
Student Screening Courses requiring entry to selection should be registered via SOL-A. *Only students who have a CNS account and who are not students of the Faculty of Policy Studies, Faculty of Environment and Information Studies, Graduate School of Media and Governance, Faculty of Nursing and Medical Care, and Graduate School of Health Management can enter via the system. Please check K-Support News for the details.	This item will appear when you log in (Keio ID required).
Lottery Method	This item will appear when you log in (Keio ID required).
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K-Number	FPE-CO-03013-211-12

Course Administrator	Faculty/Graduate School	FPE	POLICY MANAGEMENT / ENVIRONMENT AND INFORMATION STUDIES
Course Administrator	Department/Major	CO
Main Course Number	Level	0	Faculty-wide
	Major Classification	3	Fundamental Subjects (Other Than Introductory Subjects, Subjects of Language Communication)
	Minor Classification	01	Subjects of Data Science - Data Science 1
	Subject Type	3	Elective 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		12	Analysis, applied mathematics, and related fields

Course Summary

This is an introduction to the mathematical theory of probability. We begin with the basics of set theory, mathematical logic, and combinatorics, on which we build probability theory. After introducing the concept of probability, we cover fundamental topics in probability theory: conditional probability, independence, Bayes' theorem, random variables, probability distributions, expectation, variance, and the central limit theorem.

Course Description/Objectives/Teaching Method/Intended Learning Outcome

The theme of this lecture is the mathematical theory of probability with a focus on data science. Probability is, in fact, a fundamental tool in statistics, information theory, and computer science. Building on high school mathematics, we will explore several important topics in probability. The goal is to develop familiarity with this increasingly important subject so that students can freely apply basic probability theory in their respective fields of study in the future.