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 *For conditions regarding "additional permission", please refer to the "Student Screening Details" section. Approval for additional permission is at the lecturer's discretion, and is not guaranteed.	This item will appear when you log in (Keio ID required).
Screening Method *If selection is by lottery: Complete the course registration process and check your permission status on the course registration screen. If selection is by assignment: Carefully review the "Student Screening Details" section, register for the course via the "Assignment Submission URL," and submit the required assignment.	This item will appear when you log in (Keio ID required).
Expected Number of Acceptances	This item will appear when you log in (Keio ID required).
Contact(Mail)	This item will appear when you log in (Keio ID required).
Course Description	Students learn statistical science, modelling and simulation to develop mathematical reasoning skills applicable to data analysis and decision making in a variety of fields.
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.