Data Analytics for Marketing and Finance

Lecture, three hours. Enforced requisite: course 402. How to fit predictive models and visualize multivariate data using examples and topics from marketing and finance. Topics include conditional prediction and predictive models, advanced treatment of regression, visualization and graphics, automating analysis for high dimensional data. Use of industry-leading R/Rstudio statistical environment. S/U or letter grading.

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Enrollment Progress

Dec 4, 3 PM PST
LEC 1: 27/80 seats taken (Open)
LEC 2: 34/80 seats taken (Open)
First passPriority passSecond pass2 days5 days8 days11 days14 days17 days20 days23 days26 days020406080100

Section List

  • LEC 1

    Open (34 seats)

    M 1pm-3:50pm

    Gold Hall B301

  • LEC 2

    Open (28 seats)

    M 7:10pm-10pm

    Gold Hall B301

Course

Instructor
Stephen A. Spiller
Previously taught
22W 21W 20W 19W 18S

Previous Grades

Grade distributions not available.