BA 355: Business Analytics {Fall 2022}

General Course Material:   

 

Take Home Final Exam Problems

 

 

Current Notes: 

 

·       M 11/28:         CFB update, Discuss ICE 6, Google Analytics, Start Ska Case

·       W 11/30:         The Knapsack Problem, ICE 7, Excel

·       F 12/2:             Complete ICE 7, work on Case 5

·       M 12/5:           CFB prizes, work on Case 5 and THFEPs

·       W 12/7 & F 12/9:  Complete Case 5 and THFEPs by 12/12 at noon.

 

*** Case 4 Answer Key ***

 

 

 

Case 5: Ska Brewing Forecasting

 

 

 

 

Older Notes:

 

·       M 8/29: Slides.  Intro to Analytics

·       W 8/31: ICE 1

·       F 9/2:   Intro to College Football Analytics Challenge! and start Case 1

·       M 9/5: Work on Case 1, Create PivotTable

·       W 9/7:  First look at Logistic Regression

·       F 9/9:   ICE 2.  Work independently on this one, I’ll be in my office for this hour.  Also make your CFB picks (for fun and prizes) and explain them (for class points)

·       M 9/12:  Complete Logistic Regression model.

·       W 9/14:  Start Case 1.2

·       F 9/16: Case 1.1 is due.  Progress on Case 1.2.

·       M 9/19: Case 1.2.  Clean data and start analysis.

·       W 9/21: First look at Case 2.1

·       F 9/23:  ICE 3

·       M 9/26: Discuss CFB, ICE 3, Case 1.1.  Work on Case 2.1

·       W 9/28: ICE 4

·       F 9/30:  Complete ICE 4 and work on Case 2.1.

·       M 10/3: Go over Case 1.2 (re-grade?) & ICE , Work on Case 2.1/2.2.

·       W 10/5: Notes on function and EV, more Case 2.1/2.2.  Part of Case 2.1 due.

·       F 10/7:  Fall Mini-Break, No Class!!!

·       M 10/10: Finish Case 2.1, Start Case 2.2.

·       W 10/12:         First look at Case 3

·       F 10/14:           Case 2.2 and Case 3.1.  Collect data for 3.1.

·       M 10/17:         No Class!, submit Durango data for 3.1 – this is ICE 4.5 on Canvas.

·       W 10/19:         Discuss outliers, ICE 5, Case 3.1

·       F 10/21:           ICE 5 due, work on Case 3.1.

·       M 10/24:         CFB update, ICE 5 Answers, Clean Case 3.2 data, MLR

·       W 10/26:         Cases 3.1 and 3.2

·       F 10/28:           Case 3.2

·       M 10/31:         Case 3.2

·       W 11/2:           First look at Case 4

·       F 11/4:             Case 3.2, small ICE, CFB picks

·       M 11/7:           Start Case 4

·       W 11/9:           Work on Case 4, start ICE 6, Data

·       F 11/11:           Guest speakers from Ian Phillippi and Pete Iacona from Mountain Capital Partners.  On time attendance is mandatory.

·       Week 12:         Complete Case 4 and ICE 6 by 1:15pm on Friday 11/18.

Intro to BA:

 

Case 1: NFL Point Spreads

·       Case 1 Part 1   **** Answer Key ****

o   NFL Data for 2013 - 2016

o   Point Spreads and Win Percentages

o   Logistic Curve fitted with Solver

·       As published in INFORMS Transactions on Education (link)

·       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 and Loan Default Rates

·       Assignment 2

·       Case 2.1, Credit Score Data

·       ICE 4

·       Case 2.2, Data

 

*** Answer Key, Excel ***

 

Case 3: Zillow/Real Estate/Outliers

·       Case 3.1

·       ICE 5

o   Outliers file from class on 10/19

·       Multiple Linear Regression Example

·       Case 3.2

o   Clean Data

o   Raw Data

 

*** Answer Key ***

 

 

 

Case 4: Zip Codes