Regression Analysis and Design of Experiments (Spring 2023 TA)

Teaching Assistant

My primary responsibilities were grading homework assignments (6) and exams (2), while providing solutions and detailed feedback on student work to enhance students’ leaning experience. To ensure effective communication and support, I maintained a high level of organization and made sure the students’ grades were accurate, and that all documentation was up to date. I made myself readily available to students via prompt email responses, in-person and virtual office hours, and assistance both during and outside of scheduled office hours. Additionally, I closely monitored students’ progress throughout the semester and scheduled Zoom meetings with students to address any questions or concerns that arose during the course.

Textbooks

• Required Textbook: none
• Optional Textbooks:
  • Terry E. Dielman, “Applied Regression Analysis”
  • Douglas C. Montgomery, “Design and Analysis of Expedriments”

Course Description

Course begins with an applied regression module that emphasizes analysis and interpretation of real data, and statistical computing. Second part of course focuses on principles and implementation of experimental design for scientific research purposes. Standard designs presented along with the proper kinds of analysis for each. Continued emphasis on real data and statistical computing using R and/or SAS.

Student Learning Outcomes

The primary goals of this course are:

• To perform a full regression analysis of simple data.
• To interpret and summarize the results you obtain.
• To think critically about applications of regression methods in your field of study.
• Design simple experiments to test hypotheses about specified treatments
• Analyze the data you collect in a statistical software package and report on your results.
• Think critically about the design of experiments in your own work and in published work from researchers in your field.

Software

R and/or SAS.