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.
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.
Probability, Statistics, Data Analysis
✔ Specialist skills | Intercultural skills | Communication skills | Critical thinking skills | ✔ Practical and/or problem-solving skills |
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 | |
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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 |
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.
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.
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Exercise 45%, Group Work 15%, Midterm Examination 25%, Final Examination 25%
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