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140.752.71
Advanced Methods in Biostatistics II

Course Status
Cancelled

Location
Internet
Term
2nd Term
Department
Biostatistics
Credit(s)
4
Academic Year
2022 - 2023
Instruction Method
Synchronous Online
Auditors Allowed
No
Available to Undergraduate
No
Grading Restriction
Letter Grade or Pass/Fail
Course Instructor(s)
Contact Name
Frequency Schedule
One Year Only
Prerequisite

140.751

Description
Surveys basic statistical inference, estimates, tests and confidence intervals, and exploratory data analysis. Reviews probability distributions and likelihoods, independence and exchangeability, and modes of inference and inferential goals including minimizing MSE. Reviews linear algebra, develops the least squares approach to linear models through projections, and discusses connections with maximum likelihood. Covers linear, least squares regression, transforms, diagnostics, residual analysis, leverage and influence, model selection for estimation and predictive goals, departures from assumptions, efficiency and robustness, large sample theory, linear estimability, the Gauss Markov theorem, distribution theory under normality assumptions, and testing a linear hypothesis.
Learning Objectives
Upon successfully completing this course, students will be able to:
  1. Apply the theories to standard experimental designs
  2. Discuss and estimate variance components
  3. Discuss theory and application of linear mixed models
  4. Discuss the concept of best linear unbiased estimation and prediction
  5. Develop the theory of restricted maximum likelihood
  6. Discuss shrinkage estimation
Methods of Assessment
This course is evaluated as follows:
  • 50% Homework
  • 15% Midterm
  • 35% Final Exam
Special Comments

Please note: This is the virtual section of a course that is also offered onsite. Students will need to commit to the modality for which they register.