PSYC489D

Advanced Special Topics in Psychology; Data Science for Psychology and Neuroscience I

Prerequisites: MATH120, MATH130, or MATH140; and PSYC300. An introduction to programming (in R and/ or Python) and statistics from a computational perspective. Highly hands-on with a heavy emphasis on project work, and a focus on application and execution over theory, which is introduced at a high level only where needed.

Sister Courses: PSYC489A, PSYC489B, PSYC489C, PSYC489E, PSYC489F, PSYC489G, PSYC489H, PSYC489I, PSYC489J, PSYC489K, PSYC489L, PSYC489M, PSYC489N, PSYC489O, PSYC489P, PSYC489Q, PSYC489R, PSYC489T, PSYC489U, PSYC489V, PSYC489W, PSYC489X, PSYC489Y, PSYC489Z

Past Semesters

Alec Solway

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Average rating: N/A

Include P/F semesters During the Spring 2020 and Spring 2021 semesters, students could choose to take some of their courses pass-fail mid-semester which skews grade data aggregated across multiple semesters.

Average GPA of 3.62 between 47 students*

A-: 6.38%

A: 40.43%

A+: 34.04%

B-: 2.13%

B: 2.13%

B+: 2.13%

C-: 2.13%

C+: 4.26%

F: 2.13%

W: 2.13%

other: 2.13%

* "W"s are considered to be 0.0 quality points. "Other" grades are not factored into GPA calculation. Grade data not guaranteed to be correct.