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2022　Statistics and Data Analysis E

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Academic unit or major
Undergraduate major in Transdisciplinary Science and Engineering
Instructor(s)
Hanaoka Shinya  Choi Sunkyung 
Class Format
Lecture / Exercise    (HyFlex)
Media-enhanced courses
Day/Period(Room No.)
Tue7-8(H106)  Fri7-8(H106)  
Group
E
Course number
TSE.M204
Credits
2
Academic year
2022
Offered quarter
1Q
Syllabus updated
2022/4/4
Lecture notes updated
-
Language used
English
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Course description and aims

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.

Student learning outcomes

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 that will be developed

✔ 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/Required learning

  Course schedule Required learning
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 Multiple Random Variables Joint Probability Function, Correlation Analysis
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

Out-of-Class Study Time (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

Assessment criteria and methods

Exercise 45%, Group Work 15%, Midterm Examination 25%, Final Examination 25%

Related courses

  • None

Prerequisites (i.e., required knowledge, skills, courses, etc.)

None

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