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2020 Faculty Courses School of Environment and Society Undergraduate major in Transdisciplinary Science and Engineering

Statistics and Data Analysis

Academic unit or major
Undergraduate major in Transdisciplinary Science and Engineering
Instructor(s)
Shinya Hanaoka / Sunkyung Choi
Class Format
Lecture/Exercise (Zoom)
Media-enhanced courses
-
Day of week/Period
(Classrooms)
7-8 Tue (S611) / 7-8 Fri (S611)
Class
-
Course Code
TSE.M204
Number of credits
110
Course offered
2020
Offered quarter
4Q
Syllabus updated
Jul 10, 2025
Language
English

Syllabus

Course overview and goals

Through lectures and exercises, this course is designed to teach methods of statistical analysis, estimation and testing that are required for processing and understanding the data obtained by experiments, measurements and simulations.

Course description and aims

By the end of this course, students will have acquire fundamental knowledge on statistics and data analysis, which includes methods for estimating probability density distribution, testing of statistical hypotheses, correlation analysis, regression analysis and multivariate analysis.

Keywords

Probability, Statistics, Data Analysis

Competencies

  • Specialist skills
  • Intercultural skills
  • Communication skills
  • Critical thinking skills
  • Practical and/or problem-solving skills

Class flow

Each lecture will include both teaching content and exercises, and exercises will be applied to confirm understanding of the lecture content. Structure will be: Review of previous lecture: 10 minutes; lecture: 60 minutes; exercise: 20 minutes. Group work is also conducted using the skills of statistics.

Course schedule/Objectives

Course schedule Objectives
Class 1

Fundamentals of Probability

Set Theory, Random Variable, Bayesian Probability

Class 2

Basics of Probability Distributions

Probability Distribution, Normal Distribution

Class 3

Various Probability Distributions

Binomial Distribution, Poisson Distribution

Class 4

Various Probability Distributions

Exponential Distribution, Hyper-geometric Distribution

Class 5

Important theorem

Law of Large Numbers, Central Limit Theorem

Class 6

Midterm Exam

Midterm Exam

Class 7

Population and Sampling

Population, Random Sampling

Class 8

Statistical Estimation

Point Estimation, Interval Estimation

Class 9

Hypothesis Test

Statistical Hypothesis

Class 10

Principal Component Analysis

Principal Component Analysis

Class 11

Regression and Correlation Analysis

Regression Analysis, Correlation Analysis

Class 12

Quantification Theory

Quantification Theory I, II and II

Class 13

Outline and Discussion of Group Work

Outline and Discussion of Group Work

Class 14

Presentation of Group Work

Presentation of Group Work

Study advice (preparation and review)

To enhance effective learning, students are encouraged to spend approximately 100 minutes preparing for class and another 100 minutes reviewing class content afterwards (including assignments) for each class.
They should do so by referring to textbooks and other course material.

Textbook(s)

Alfred H-S. Ang and Wilson H. Tang (2007) Probability Concepts in Engineering, Emphasis on Application in Civil and Environmental Engineering, John Wiley & Sons. New York.

Reference books, course materials, etc.

None

Evaluation methods and criteria

Exercise 35%, Group Work 15%, Midterm and Final Examination 50%

Related courses

  • None

Prerequisites

None