BA 355: Business Analytics {Fall
2019}
General Course Material:
First Half Material:
Notes: Tu 9/2: ICE 1, Th 9/4, Tu 9/10: Work
on Case 1.1, Th 9/12: Fit general logistic function to data, Tu 9/17: Clean
2017 data, Case 1.2, Th 9/19: More Case 1.2, Start Case 1.3, Tu 9/24, Th 9/26: Work on
Case 2, Tu 10/1: Return/Discuss Case 1.2, Work on Case 2, Th 10/3: Discuss
make-up for Case 1.2, show NCAA curve, catch up
on Case 2 and Case 1.3.
Tu
10/8: ICE 2 (Data), Th 10/10: Case 2
Extensions, Tu 10/15:
Start Case 3, Th 10/17: Outliers, ICE 3, Tu 10/22: No Class!,
Th 10/24: Case 3.1, Tu 10/29: Case 3.2, discuss Zillow accuracy
Intro to BA:
Case 1: NFL Point Spreads
·
NFL
Data for 2013 - 2016, Point Spreads and Win
Percentages
·
Data with
fitted general logistic function – file
created in class on Th 9/12.
·
What to do with four
ties from 2013 – 2016? For underdog, a
tie is a win? https://en.wikipedia.org/wiki/1968_Yale_vs._Harvard_football_game
Case 2: Credit Scores/Probability of Default
·
Case
2
Case 3: Zillow/Real Estate Data
·
Case 3.1
·
ICE 3
·
Case 3.2 (Due
Tuesday 11/5)
Second Half Material:
Notes: Th 10/31: Complete Case 3.2, Tu 11/5, Th 11/7: Modified
Tukey’s Rule, Start Case 4, Tu 11/14: Start Case 5, Th 11/16: Work on Cases 4
and 5, Week 12: Work on Cases 4 and 5,
at least one of them must be turned in by Thursday 11/21, Tu 12/3, Th 12/5: Work on Cases 5 and 6, Last Week! Work on
Case 5, Case 6 and Take Home Final Exam – all due on Tuesday
12/17 by 4pm.
Knapsack
Problem
·
Example
Case
4: Forecasting at Ska Brewing Company
Case 5: Zip Codes
Case
6: Create an ICE or Case Study