Syllabus

Course Topics

  1. Statistics Fundamentals
  2. Linear Regression
  3. Generalized Linear Models

Learning Objectives

  1. Fit and interpret statistical models, including linear and generalized linear models.
  2. Connect statistical modeling concepts to underlying statistics fundamentals including probability distributions and estimation.
  3. Map a research question and dataset to the appropriate statistical model.
  4. Make careful and critical decisions about model building and consider real-world implications.
  5. Communicate (through written and oral communication) model results to a broad audience.

Course Materials

Textbooks:

Statistics for Data Scientists: An Introduction to Probability, Statistics, and Data Analysis by Kaptein, M. and van den Heuvel, E. (Available through the Duke Library)

An Introduction to Statistical Learning with Applications in R, 2nd edition by James, G., Witten, D., Hastie, T., and Tibshirani, R. (Available online)

Statistical Foundations, Reasoning and Inference For Statistics and Data Science by Kauermann, G., Küchenhoff, H., and Heumann, C. (Available through the Duke Library)

Course Materials

Assignments will be submitted on Gradescope (access code in the syllabus on the course website)

Announcements will be posted on the #ids702-fall24 Slack channel in the MIDS Workspace. You’re also welcome to post questions or resources here!

Office Hours & Communication

Andrea: Thursday after class (4:30-5:30) in the classroom if available or my office (Gross 223 - by the lockers)

Jiayi: Tuesday 12-1, Gross Hall 230N

Rakeen: Monday 3:30-4:30, Gross Hall 230N

Revanth: Wednesday 12-1, Gross Hall 230N

Communication: Slack or email; follow up after 24 hours on weekdays

Course components

  1. Class preparation/quizzes
  2. Application exercises
  3. Homework assignments
  4. Statistics Reflections
  5. Midterm exam
  6. Final project

Course Policies

  • Late submissions:

    • 50% credit within 24 hours

    • One no-questions-asked 24-hour extension for homework or statistics reflection

    • No make-up assignments

  • Academic integrity:

    • As a Duke student, you agree to uphold the Duke Community Standard

    • Read Nick Eubank’s advice on using ChatGPT

Resources

  • Duke Counseling and Psychological Services (CAPS)

  • Student Disability Access Office (SDAO)

  • Academic Resource Center (ARC)