Analytic Methods For Mining Hlthcre Data

Instructor:
Richard Charnigo
Xiaohua Douglas Zhang
636
Credits:
3.0
001
Building:
W T Young Library
Room:
Rm.B-35
Semester:
Spring 2023
Start Date:
End Date:
Name:
Analytic Methods For Mining Hlthcre Data
Requisites:

Prereq: BST 600 and BST 635 or consent of instructor.

Class Type:
LEC
3:30 pm
4:45 pm
Days:
TR
Note:
"Students without BST 635 but who have coding experience in R or another statistical or programming language are permitted to enroll in this semester's offering of BST 636. Please contact the instructor for more information."

BST 636 covers statistical techniques for issues associated with the exploration of large public health data sets and the development of models from such data sets. The practical issues involved in analyzing large observational healthcare data will be addressed with a focus on appropriate interpretations and the effective communication of results.

BST 636 covers statistical techniques for issues associated with the exploration of large public health data sets and the development of models from such data sets. The practical issues involved in analyzing large observational healthcare data will be addressed with a focus on appropriate interpretations and the effective communication of results.

BST