3KE3 Management of Enterprise Data Analytics - RStudio: Prescriptive Analytics Assignment (III)
RStudio: Prescriptive Analytics Assignment (III)
Assignment Overview
Objective
Providing some hands-on experience with the RStudio to see how it can be used in decision-making. Therefore, throughout this assignment, you are expected to use appropriate codes to accomplish the required tasks as efficiently as possible.
Grade
This assignment is worth 7.5% of your total course grade. There are two parts in this assignment, and each part contains a set of questions. See the marking scheme:
Part 1 60 marks Part 2 40 marks Total 100 marks
The overdue penalty is 20% of the total assignment mark per day.
Submitting the Assignment
Submit MS Word or PDF file, in addition to TWO RStudio scripts (for each part, one RStudio script should be submitted). If you submit more than one file, the most recent will be graded. Please name the file as "Class section-Student number-First name-Last name" (for example, if you are in section 1 and your name is John Smith and your student number is 1234567, name the files C01-1234567John-Smith).
The Word File
Create an MS Word file that includes the answers to the questions and any screenshots, graphs, and tables as instructed in the assignment questions. You will need to submit the finalized version of this file (as either Word or PDF ) to receive the grades for the assignment.
For Windows users:
- First, download R using the following link: https://cran.r-project.org/bin/windows/
- After downloading and installing R, you can download RStudio from the RStudio website: https://www.rstudio.com/products/rstudio/download/ For Mac users:
- First, download R using the following link: https://cran.r-project.org/bin/macosx/
- After downloading and installing R, you can download RStudio from the RStudio website: https://www.rstudio.com/products/rstudio/download/
For the instruction of R and RStudio installation, you can search online. There are lots of resources. For instance, check the following link for Windows and Mac users: https://www.dataquest.io/blog/installing-r-on-your-computer/
Notes: For each part, you need to interpret the results from each analysis to help a manager make proper decisions.
Part 1.
A manufacturing company produces three products: Product A, Product B, and Product C. The company wants to determine how many units of each Product to produce to maximize the profit. Each unit of Product A requires 2 units of labor, 3 units of material X, and 1 unit of material Y, and will be sold for $20. Each unit of Product B requires 4 units of labor, 2 units of material X, and 2 units of material Y, and will be sold for $25. Each unit of Product C requires 4 units of labor, 1 unit of material X, and 3 units of material Y, and will be sold for $22. The company has 475 units of labor, 400 units of material X, and 300 units of material Y available. 1.1. How many Products, A, B, and C, should the company produce to meet the goal? 1.2. Interpret the results you obtain in RStudio in a short paragraph. (e.g., you can mention which Product is (not) profitable and why).
1.3. Assume that the number of Products A, B, and C to be produced are fixed and equal to the optimal values you found in question 1.1. By changing the values of the coefficients in the objective function, determine the highest profit given the specified number of products. What are the new coefficients? Explain your approach to solving this question. Note. It is fine if you observe slight changes in the amount of decision variable values (for example, ±5) 1.4. Assume that the manager has decided not to sell product B. Based on this input, draw a plot that shows the constraints and the objective function of this problem. Add the screenshot of the plot to your report and interpret the results. (Assign Product A to Y-axis and Product C to X-axis)
Part 2. Assume that you are an investor, and you want to invest in one of the following manufacturing companies:
Company A: A beverage company produces three products: cola, lemonade, and iced tea. The profit margin of each unit of cola, lemonade, and iced tea are $5, $7, and $6, respectively. The monthly production distribution of cola, lemonade, and iced tea is as follows: Cola: Normal with mean 100 and variance 25 Lemonade: Normal with mean 70 and variance 36 Iced tea: Normal with mean 50 and variance 9.
Company B: A toy company produces three products: dolls, cars, and puzzles. The profit margin of each doll, car, and puzzle are $4, $8, and $6, respectively. The monthly production distribution of dolls, cars, and puzzles is as follows: Dolls: Normal with mean 70 and variance 16 Cars: Normal with mean 60 and variance 9 Puzzles: Normal with mean 40 and variance 25. 2.1. Which of these companies would you choose to invest in (company A or B)? Why? 2.2. How many units of cola, lemonade, and iced tea should company A produce to obtain its optimum profitability? 2.3. How many dolls, cars, and puzzles should company B produce to obtain its optimum profitability? (Note. Set seed to 50 in RStudio, and produce 100 random variables for each of the products)
