CIVL 7012/8012

Probabilistic Methods for Engineers

Syllabus

Lecture 1: Collection and analysis of data

Lecture 1.1: Basic axioms of probability (self reading)

Lecture 2: Discrete distributions

In class example solutions: Discrete distributions

Lecture 2.1: Poisson distribution derivation (self reading)

Lecture 3: Continuous distributions

In class example solutions: Continuous distributions

Lecture 4: Multivariate distributions

In class example solutions: Multivariate distributions

Lecture 5 : Confidence intervals

In class example solutions: Confidence intervals

Lecture 6 : Selecting a distribution

Spreadsheet on selecting distributions

Lecture 7 : Practice problems on hypothesis testing

In class example solutions: Hypothesis Testing

Lecture 8 : Simple Linear Regression I Recording

Lecture 9 : Simple Linear Regression II Recording

SLR Spreadsheet

Lecture 10 : Simple Linear Regression III Recording (stop at 30 min)

Lecture 11: ANOVA Recording (start at 30 min)

ANOVA example

Lecture 12 : Multiple Linear Regression Recording

Lecture 13 : Categorical Variables in Multiple Regression Recording (stop at 45 min)

Lecture 14: Multicollinearity and validation Recording (start at 45 min)

Lecture 15 : Discrete choice models Recording

Discrete choice model example

Lecture 16 : SLR and MLR in-class problems

SLR and MLR in class solutions-Excel Recording (stop at 45 min )

SLR and MLR in class exercise-R Recording (start at 45 min )

Lecture 17: Correlation between variables Recording

Correlation between variables-spreadsheet example

Lecture 18.1 : Time series data Recording

Lecture 18.2 : Modeling time series data (Only for reference-Not covered in class)

Lecture 19 : Count data models Recording

Lecture 20 : Introduction to Machine Learning Recording

Lecture 21 : Review of course and final exam Q&A Recording

Final Exam during class time (May 4, 2020)

Final report due (Noon, May 5, 2020)