02_sync_ModelDBT
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Michigan State University *
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GB519
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Feb 20, 2024
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Week 2 Synchronous F2F Meeting: Participation Assignment
“Model Design, Build, & Test”
GB730 - Modeling & Optimization for Business Analytics
Professor Jordan Tong
Overview
This participation assignment corresponds to our F2F class meeting on Thursday. Input your answers to the questions below on the associated Canvas quiz. Use the table of contents on the left of this page to help you navigate if you wish. As with all participation assignments, you are encouraged to collaborate with your classmates. However, straight copying of files/answers is not allowed. Recall that all participation assignments are graded primarily on effort and completeness, not correctness (see syllabus).
Learning Objectives:
●
Practice and improve spreadsheet model designing, building, and testing skills
●
Explore using ChatGPT to build models from prompts
●
Improve ability to code simple models in Python utilizing lists and for loops
Warm Up
Question 1 [Free Response]
Who’d you work on this participation assignment with today? If you are working by yourself for whatever reason, just report that.
Spreadsheet Modeling Build & Test
Question 2 [File Upload]
Here is the non-redacted office building problem instructions
. Within your team, discuss the sketch of your models. Then, after we discuss in class, build it (each of you should build your own).
For your reference, I got $690,988.79. If you disagree, try to understand clearly why. Then, upbload your completed Excel model. For participation credit, you need to submit something reasonable for this question.
Question 3 [Free Response]
Let’s examine the above office building problem using ChatGPT in your group. Explore and discuss with your classmates as you do it. Respond to the following questions:
1.
When you (or ideally, multiple students) directly copy and paste the prompt into ChatGPT, what answer do you get? Is it consistent with yours? 1
2.
Next, ask ChatGPT to produce Python code to try to answer the prompt. Then examine and run the code it provides. What answer do you get? Is it consistent with yours?
3.
Reflect on your above two experiences (and chat with your neighbors about it if you have time). What are some pros and cons about leveraging ChatGPT for this kind of exercise? How might you adapt your prompts to leverage ChatGPT in a way that’s more useful? (A couple of sentences is sufficient, but you can comment more if you’d like.)
>>>>>>>>>> Please pause here until after the break <<<<<<<<<<<<<<<<<<<<
From Excel to Python
Question 4 [Code copy and paste]
In class, I demonstrate how to build a model for the Advertising Budget Problem
in Python. Please follow along by building a version of your own. For your reference, here is my completed
spreadsheet model to the Advertising Budget problem: 02_sync_AdBudgetCompleted.xlsx
. Then, copy and paste your code into the box below.
Question 5 [Code copy and paste]
Model the office building problem in Python. It may be good practice to try to do it straight from your ID and the instructions (i.e., without
referring to your excel sheet), but of course you may also wish to refer to your completed Excel model. Copy and paste your CODE. It’s OK if you don’t finish, but please put some code in to demonstrate your participation.
Question 6 [File Upload]
This is an OPTIONAL question. You can leave it blank without penalty. I know some of you are faster at Python than others, which is totally OK.
Recall P7 from the warm-up modeling problems (restated below). Can you code up a model in Python for this problem? (Note: depending on where you feel you need practice, you may wish to ID the problem first.). For your reference, here is the solved Excel model
. Copy and paste your CODE below. Again, if you don't get to this problem, do not worry -- simply
leave it blank.
Problem 7: Profit Projection
Your boss is asking you to estimate the total profit they'll earn for a service product over the next 6 months. Your company plans to price the product at $120 per unit each month, except they will offer a sale in month 3 for $100 per unit, and a sale in month 6 for $80 per unit.
To help you predict sales in a given month, your analysts have collected some basic price elasticity data shown in the table below (your boss says you can simply use a linear regression model based on this data to predict how price affects sales in each month -- and if you don't know how to do that in Python, you can simply do it in Excel):
Price
Units Sold
2
$70
205
$80
184
$90
147
$100
125
$110
109
$120
105
$130
75
$140
55
You asked your boss for some cost figures. They said their current best guess for the first month is that fixed costs are about $500 per month and variable costs are about $60 per unit each month. But they think the fixed costs are growing at about 2% each month.
3
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