BA 355: Business Analytics {Fall 2023}

General Course Material:   

• Syllabus
• Canvas
• *** College Football Challenge *** For fun and prizes (not graded).

Second Half of Semester Notes:

· M 10/30: Complete Case 3.1, Google Analytics

· W 11/1: Work on Case 3.2

· M 11/6: Complete Case 3.2, Start Case 4

· W 11/8: Case 3.2 due. Work on Case 4a) – be proactive on this one.

· M 11/13: Work on Case 4. Specifically make sure you can do parts c), f) and g).

· W 11/15: Complete Case 4, due on Friday 11/17 by 12:15pm.

· M 11/27: Case 4 (due Wednesday), Start Case 5: Ska Forecasting

· W 11/29: Case 5

· M 12/4: Course Review: Concepts, Methods, Big Picture

Case 3: Zillow Real Estate Models

· Case 3.1

· ICE 4

o Outliers file from class on 10/9

· Multiple Linear Regression Example

· Case 3.2

o Data

*** Case 3.2 Answer Key ***

Case 4: Zip Codes

• Original Request
• FLC data 2015.xlsx
• Case 4
• Distance Formula: http://bluemm.blogspot.com/2007/01/excel-formula-to-calculate-distance.html
• Database source 1: http://federalgovernmentzipcodes.us/
• Hints:
• =vlookup() – make sure data are sorted by zip code
• Straight line distance estimates can be found from lat and long
• Map function in Excel
• Case (As published in INFORMS Transactions on Education)

Case 5: Ska Brewing Forecasting

• Case 5 (Updated!)
• Data
• Original Case (As published in The Applied Business Analytics Casebook: Applications in Supply Chain Management, Operations Management, and Operations Research)

Older Notes and Material Below This Point

· M 8/28: Slides. Intro to Analytics; ICE 1

· W 8/30: Bubbles, Solver, Intro to CFB Analytics Challenge! and start Case 1.1

· M 9/4: Continue working on Case 1.1, Re-create Case 1.2

· W 9/6: Fit Curves to data

· M 9/11: New classroom EBH 118;

· W 9/13: ICE 2

· M 9/18: Start Case 1 Part 2 – for real this time!

*** Case 1.1 Answer Key ***

· W 9/20: Billy Walters video, first look at Case 2, continue Case 1 Part 2

· M 9/25: Complete Case 1.2, Start Case 2.1

· W 9/27: Discuss class meetings, ICE 3

· M 10/2: Cases 2.1

· W 10/4: Finish Case 2.1, ICE 3

· M 10/9: First look at Case 3.1, discussion of outliers. Outliers

· W 10/11: Hybrid Day: CFB Assignment, ICE 4 and Durango Zillow Data due.

· M 10/16: Complete Case 2.2.

*** Case 2.2 Answer Key with Excel ***

· W 10/18: Meet in class. Multiple Regression, work on Case 3.1, Start Case 3.2.

· M 10/23: Guest speakers: Blake and Dan. Work on Case 3.1.

· W 10/25: Case 3.2

Intro to BA:

• Assignment 1
• ICE 1 (Bubbles Data)
• ICE 2

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Case 1: NFL Point Spreads

· Case 1 Part 1

o NFL Data for 2013 - 2016

o Point Spreads with Ties Eliminated

· 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

• Stern Paper
• On the (Non-Linear) Probability of Winning
• What is home field advantage worth?
• Case 1 Part 2

Case 2: Credit Scores and Loan Default Rates

· Assignment 2

· Case 2.1, Credit Score Data

· ICE 3

· Case 2.2, Data