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<\/span> <\/strong><\/a><\/div><\/div><\/div><\/span>Book info for this course<\/a><\/div>
BST 636Section 001<\/span><\/h4>
Analytic Methods for Mining Hlthcre Data<\/span>3.0 Credits<\/span><\/span><\/h5><\/div>
Prereq: BST 600<\/a> and BST 635<\/a> or BST 535<\/a> or consent of instructor.<\/strong><\/p>
"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."<\/p>
Offered in Fall Semester 2016<\/span><\/h4><\/span><\/span>
Credit from this course applies to the following programs: Graduate, Graduate Professional<\/strong><\/p>
BST 636<\/a> 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.<\/p>
View offering history<\/strong><\/span><\/a><\/p><\/div><\/div>
Course Deadlines & Refund Schedule<\/h4><\/div>
EVENT<\/div>
DEADLINE DATE(S)<\/div>
ADDITIONAL INFORMATION<\/div>
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Add Class<\/strong><\/div>
1/13/2023<\/div>
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Change Grade Type<\/strong><\/div>
1/27/2023<\/div>
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Drop Class<\/strong><\/div>
1/27/2023<\/div>
Class will not appear on the transcript<\/div><\/div><\/div>
Withdraw from Class<\/strong><\/div>
1/28/2023 - 3/27/2023<\/div>
Class will appear on the transcript with a \'W\' grade<\/div><\/div><\/div>
100% Refund/Reduction Received<\/strong><\/div>
1/8/2023<\/div>
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80% Refund/Reduction Received<\/strong><\/div>
1/9/2023 - 1/13/2023<\/div>
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50% Refund/Reduction Received<\/strong><\/div>
1/14/2023 - 2/8/2023<\/div>
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0% Refund/Reduction Received<\/strong><\/div>
2/9/2023 - 3/27/2023<\/div>
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