Instructor Information

H.M. James Hung

Work Phone: 301-796-1092

Course Information

Course Description

Introduction to regression and linear models including least squares estimation, maximum likelihood estimation, the Gauss-Markov Theorem, and the Fundamental Theorem of Least Squares. Topics include estimation, hypothesis testing, simultaneous inference, model diagnostics, transformations, multicollinearity, influence, model building, and variable selection. Advanced topics include nonlinear regression, robust regression, and generalized linear models including logistic and Poisson regression.


EN.625.603 Statistical Methods and Data Analysis, multivariate calculus, and basic knowledge of matrix and linear algebra.

Course Goal

To introduce statistical methods for regression analysis and model building for studying relationship between variables and develop tools for model diagnostics and validation and then apply these methods and tools to real case studies.

Course Objectives

  • Draw out a plan and process for statistical model building.

  • Develop statistical methods for regression model analysis following statistical principle.
  • Perform statistical modeling, model diagnostics and validation.
  • Identify and apply appropriate analysis methods with statistical modeling to real-world applications.

When This Course is Typically Offered

This course is typically offered as an online course in the fall, spring and summer terms.


  • Simple Linear Regression
  • Multiple Linear Regression
  • Polynomial Regression
  • Indicator Variable
  • Multicolllinearity
  • Model Checking, Diagnostics, Transformations
  • Model Building and Validation
  • Nonlinear Regression
  • Generalized Linear Models
  • Nonparametric Regression

Student Assessment Criteria

Preparation and Participation: Discussion Forum 20%
Assignments 30%
Tests 30%
Course Project 20%

Assignments, tests, discussions, and course project report are due according to the dates posted in your Blackboard course site. You may check these due dates in the Course Calendar for the corresponding modules.  See course syllabus for details when the course site are available.

Computer and Technical Requirements

There is no required software to purchase. You are free to use any mathematical or statistical software, such as MATLAB, R, SAS, MINITAB, web-based statistical software, to help with computations.

Participation Expectations

See course syllabus for details when the course site is available.


Textbook information for this course is available online through the MBS Direct Virtual Bookstore.

Course Notes

There are notes for this course.

Final Words from the Instructor

The course outline and the syllabus will be provided a few days before the course site is available.

(Last Modified: 12/31/2021 08:34:13 PM)