140.731.41
Statistical Theory I
- Location:
- Internet
- Term:
- 1st term
- Department:
- Biostatistics
- Credits:
- 4 credits
- Academic Year:
- 2022 - 2023
- Instruction Method:
- Synchronous Online
- Class Times:
-
- M W, 10:30 - 11:50am
- Auditors Allowed:
- No
- Undergrads Allowed:
- No
- Grading Restriction:
- Letter Grade or Pass/Fail
- Course Instructor:
- Contact:
- Elizabeth Ogburn
- Resources:
- Prerequisite:
Linear algebra; matrix algebra; real analysis; calculus.
- Description:
-
Introduces probability and inference, including random variables; probability distributions; transformations and sums of random variables; expectations, variances, and moments; properties of random samples; and hypothesis testing.
- Learning Objectives:
-
Upon successfully completing this course, students will be able to:
- Manipulate and describe random variables
- Derive and describe the properties of hypothesis tests and point estimates from random samples
- Methods of Assessment:
This course is evaluated as follows:
- 55% Homework
- 15% Class participation
- 30% Final Exam
- Instructor Consent:
Consent required for some students
- Consent Note:
Consent required for any students who are not in the Biostatistics PhD program
- For consent, contact:
- Special Comments:
Please note: This is the virtual/online section of a course that is also offered in-person. Students will need to commit to the modality for which they register.One 1-hour lab per week (time TBA)