QAC 323
Spring 2019
| Section:
01
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| Crosslisting:
CIS 323 |
| Certificates: Applied Data Science |
| Course Cluster: Data Analysis Minor |
This course introduces the applied principles of Bayesian statistical analysis. The Bayesian paradigm is particularly appealing in research where prior research and historical data are available on parameters of interest. This course will teach students appropriate techniques for analyzing data of this nature as well as broaden computational skills in R. The course will lay the foundation for Bayesian data analysis that students can use to further develop skills in decision making. |
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| Credit: .5 |
Gen Ed Area Dept:
NSM QAC, SBS QAC |
| Course Format: Laboratory Course | Grading Mode: Graded |
| Level: UGRD |
Prerequisites: MATH132 OR ECON300 OR [GOVT367 or QAC302] |
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Fulfills a Requirement for: (CADS)(DATA-MN)(PSYC) |
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Past Enrollment Probability: 75% - 89% |
| SECTION 01 - 4th Quarter | | Special Attributes: CQC |
| Instructor(s): Ouyang,Ning Times: ..T.R.. 10:20AM-11:40AM; Location: PAC100; |
| Total Enrollment Limit: 16 | | SR major: 0 | JR major: 0 | | |
| Seats Available: 10 | GRAD: X | SR non-major: 6 | JR non-major: 6 | SO: 4 | FR: 0 |
| Drop/Add Enrollment Requests | | | | | |
| Total Submitted Requests: 0 | 1st Ranked: 0 | 2nd Ranked: 0 | 3rd Ranked: 0 | 4th Ranked: 0 | Unranked: 0 |
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