140.751.71
Advanced Methods in Biostatistics I
Cancelled
 Location:
 Internet
 Term:
 1st term
 Department:
 Biostatistics
 Credits:
 3 credits
 Academic Year:
 2022  2023
 Instruction Method:
 Asynchronous Online with Some Synchronous Online
 Auditors Allowed:
 No
 Undergrads Allowed:
 No
 Grading Restriction:
 Letter Grade or Pass/Fail
 Course Instructor:
 Contact:
 Martin Lindquist
 Frequency Schedule:
 One Year Only
 Resources:
 Prerequisite:
140.673674 & elementary course in matrix algebra; students must also register for 140.752
 Description:

Introduces students to applied statistics for biomedical sciences. Illustrates the motivations behind many of the methods explained in 140.752756. Focuses on analyzing data and interpreting results relevant to scientific questions of interest. Presents various case studies in detail and provides students with handson experience in analyzing data. Requires students to present results in both written and oral form, which in turn requires them to learn the software package R and a handful of statistical methods. General topics covered include descriptive statistics, basic probability, chance variability, sampling, chance models, inference, and regression.
 Learning Objectives:

Upon successfully completing this course, students will be able to:
 Review key concepts in linear algebra
 Lise random vectors and matrices
 Develop the least squares approach for linear models
 List projections in vector spaces
 Discuss the connection between least squares and maximum likelihood approaches
 Discuss estimability, and in particular, the Gauss Markov theorem
 Discuss the distribution theory under normality assumptions
 Compare least squares to generalized least squares
 Describe the concept of testing linear hypothesis
 Compare approaches to calculate simultaneous confidence intervals
 Methods of Assessment:
This course is evaluated as follows:
 50% Homework
 15% Midterm
 35% Final Exam
 Enrollment Restriction:
Biostatistics 1styear PhD students.
 Instructor Consent:
Consent required for all students
 Consent Note:
Consent required for all students
 For consent, contact:
 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.