2024 Faculty Courses School of Environment and Society Undergraduate major in Transdisciplinary Science and Engineering
Statistics and Data Analysis J
- Academic unit or major
- Undergraduate major in Transdisciplinary Science and Engineering
- Instructor(s)
- Shinya Hanaoka / Fumitake Takahashi / Hiroshi Sagara / Kashin Sugishita
- Class Format
- Lecture/Exercise (Face-to-face)
- Media-enhanced courses
- -
- Day of week/Period
(Classrooms) - 7-8 Tue / 7-8 Fri
- Class
- J
- Course Code
- TSE.M204
- Number of credits
- 110
- Course offered
- 2024
- Offered quarter
- 1Q
- Syllabus updated
- Mar 17, 2025
- Language
- Japanese
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 | Midterm Examinaiton | Midterm Examinaiton |
| Class 6 | Population and Sampling | Population, Random Sampling |
| Class 7 | Statistical Estimation | Point Estimation, Interval Estimation |
| Class 8 | Hypothesis Test | Statistical Hypothesis |
| Class 9 | Principal Component Analysis | Principal Component Analysis and Exercise |
| Class 10 | Regression Analysis | Regression Analysis |
| Class 11 | Factor Analysis and Discriminant Analysis | Factor/Discriminant Analysis and Exercise |
| Class 12 | Outline and Discussion of Group Work | Outline and Discussion of Group Work |
| Class 13 | Multiple Regression Analysis | Multiple Regression Analysis and Exercise |
| 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 Examination 25%, Final Examination 25%
Related courses
- None
Prerequisites
None