The following directory lists the graduate courses which the University expects to offer, although the University in no way guarantees that all such courses will be offered in any given academic year, and reserves the right to alter the list if conditions warrant. Click on the links below for a list of courses in that subject area. You may then click “View Classes” to see scheduled classes for individual courses.
5405. Applied Statistics for Data Science
3.00 credits
Prerequisites: Instructor consent and undergraduate course in statistics. Not open to students who have passed STAT 5505 or STAT 5605 or BIST 5505 or BIST 5605.
Grading Basis: Graded
Statistics essential for data science incorporating descriptive statistics; integrative numerical description and visualization of data; graphical methods for determining and comparing distributions of data; data-driven statistical inference of one-sample, two-sample, and k-sample problems; linear regression; non-linear regression; and dependent data models.
Last Refreshed: 15-APR-24 05.20.10.650542 AM
| Term | Class Number | Campus | Instruction Mode | Instructor | Section | Session | Schedule | Enrollment | Location | Credits | Grading Basis | Notes | |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 1243 5883 1 001 | Spring 2024 | 5883 | Storrs | Online Asynchronous | Ravishanker, Nalini Guo, Jieyu Zhong, Kelin |
001 | Reg | 16/40 | No Room Required - Online | 3.00 | Graded | ||
| 1248 8783 1 001 | Fall 2024 | 8783 | Storrs | In Person | Ravishanker, Nalini | 001 | Reg | TuTh 11:00am‑12:15pm |
0/45 | AUST 313 | 3.00 | Graded |