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 acquired fundamental knowledge on statistics and data analysis, which includes methods for estimating probability density distribution, testing of statistical hypotheses, correlation analysis, regression analysis, multivariate analysis and time series analysis.
Probability, Statistics, Data
|Intercultural skills||Communication skills||Specialist 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.
|Course schedule||Required learning|
|Class 1||Fundamentals of Probability||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||Important theorem||Law of Large Numbers, Central Limit Theorem|
|Class 5||Population and Sampling||Population, Random Sampling|
|Class 6||Statistical Estimation||Point Estimation, Interval Estimation|
|Class 7||Hypothesis Test||Statistical Hypothesis|
|Class 8||Regression and Correlation Analysis||Regression Analysis, Correlation Analysis|
|Class 9||Principal Component Analysis||Principal Component Analysis|
|Class 10||Outline and Discussion of Group Work||Outline and Discussion of Group Work|
|Class 11||Quantification Theory||Quantification Theory I, II and II|
|Class 12||Other Multivariate Analysis||Factor Analysis, Cluster Analysis|
|Class 13||Presentation of Group Work||Presentation of Group Work|
|Class 14||Time Series Analysis||Time Series Analysis, ARIMA|
|Class 15||Stochastic Process||Stochastic Process, Markov Process|
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.
Exercise 45%, Group Work 15%, Final Examination 40%