CIVL 7906/8906

Statistical and Econometric Methods for Transportation Data Analysis

Syllabus

Lecture-1: Introduction to Econometrics

Lecture-2: Simple Regression Model Properties

Lecture-3: Multiple Linear Regression-Properties

Lecture-4: Multiple Linear Regression- Estimation

Lecture-5: Multiple Linear Regression-Inference

Lecture-6: Multiple Linear Regression-Scale, and Interaction Effects

Homework-1: HW-1; Datasets: TRT, VOTE1, VOTE1_description, HPRICE, HPRICE_description

Lecture-7: Dummy Variable, Interaction and Linear Probability Model

Lecture-8: Heteroskedasticity-I

Lecture-9: MLR Model Selection in R [R Code] [Spreadsheet Comparison]

Lecture-10: Heteroskedasticity-II and MLR Variants

Lecture-11: Time Series-I

Lecture-12: Time Series-II

Lecture-13: Panel Data-I

Lecture-14: Panel Data-II

Lecture-15: Mid-term

Lecture-16: Instrumental Variables

Lecture-17: R-time series demonstration [R-code and data]

Lecture-18: Count data models

Lecture-19: Count data models [R Code] [Reading]

Lecture-20: Introduction to discrete choice models (Binary logit and multiunomial logit models)

Lecture-21: Discrete choice models-II

Lecture-22: Student Presentation-I

Lecture-24: Nobel laurate lecture presentation

Lecture-25: Study week

Lecture-26: Final exam