Fundamentals of Analytics and Business Intelligence

MMIS 671: Fundamentals of Analytics and Business Intelligence

Final Exam, Fall 2018

Due by 9 am on Tuesday, December 4, 2018

Maximum Score: 35 Points.

Name: ________________________________________

· Please answer the questions and submit a single consolidated document by the due date.

· Late penalty 20 points

· You may use any reference material, but there should be no collaboration or consultations.

· Penalty for any collaboration 30 points

· The last 4 pages specify the format for presenting your solutions.

· Please let me know in class on November 27 if you need any clarifications.

Problem 1. Optimization Models [10 Points]

A company produces and sells two types of coolants (C1 and C2) by mixing three grades of solvents (A, B, and C) in different proportions.

Minimum percentages of grade A solvent and maximum percentages of grade C solvent allowed for each type of coolant are specified. The company has to produce at least a specified minimum quantity of each type of coolant. The table below presents these requirements, along with the selling price of each type of coolant.

Minimum percent of

grade A allowed

Maximum percent of

grade C allowed

Minimum Quantity Required

(gallons)

Selling price

per gallon

C1 40% 30% 100,000 $4
C2 20% 60% 100,000 $3

Availability of the three grades of solvents and their costs are as follows:

Grade A B C
Maximum quantity available per day (gallons) 60,000 60,000 90,000
Cost per gallon $3 $2 $1

The company wants to maximize profits subject to the specified constraints.

Formulate the problem as a linear program, find the optimal solution, and answer the following questions:

a. What is the maximum profit attainable? [3 Points]

b. How many gallons of each solvent are used to produce each type of coolant under the optimal solution? [3 points]

c. At most how much should the company be willing to pay for one additional gallon of grade A solvent (beyond its current availability of 60,000 gallons)? [4 points]

Problem 2. Linear Regression [10 Points]

The data file “trainFinal.csv” contains observations on 12 variables: class, x1, x2, …, x10, y

Run a regression to predict the output variable y based on the 10 input variables x1, x2, …, x10.

(a) [5 Points]

Interpret the regression results to complete the table below. Specify the coefficient estimates (rounded to 2 decimal places) under the column “Coefficient Estimate”. Specify whether the coefficient estimates are significant (Yes or No) at the 0.1% level under the column “Significant”

  Coefficient Estimate Significant?
Intercept    
x1    
x2    
x3    
x4    
x5    
x6    
x7    
x8    
x9    
x10    

(b) [5 Points]

Predict the expected value of y for the 10 examples in the data file “newFinal.csv” and report the predicted values (rounded to 1 decimal place) in the table below.

x1 x2 x3 x4 x5 x6 x7 x8 x9 x10 y
0.36 0.30 0.68 0.38 0.02 0.61 0.53 0.52 0.35 0.78  
0.23 0.79 0.59 0.53 0.77 0.07 0.90 0.37 0.18 0.34  
0.80 0.96 0.35 0.69 0.19 0.59 0.85 0.55 0.75 0.68  
0.56 0.48 0.80 0.85 0.50 0.23 0.22 0.65 0.84 0.31  
0.75 0.39 0.47 0.02 0.19 0.23 0.99 0.03 0.65 0.87  
0.55 0.44 0.62 0.09 0.53 0.45 0.91 0.52 0.33 0.62  
0.20 0.70 0.24 0.81 0.22 0.01 0.82 0.67 0.40 0.46  
0.68 1.00 0.00 0.86 0.06 0.63 0.47 0.45 0.03 0.30  
0.08 0.49 0.97 0.08 0.68 0.82 0.89 0.82 0.47 0.96  
0.27 0.33 0.69 0.77 0.26 0.52 0.23 0.23 0.50 0.34  

Problem 3. Classification Tree Inductive Learning [10 Points]

Train a decision tree classifier using the observations from the data file “trainFinal.csv” to classify the output binary variable “class” based on the 10 input variables: x1, x2, …, x10.

(a) [4 Points]

Specify the rules obtained in the form:

IF <Condition> Then class = ?

(b) [3 Points]

Use the rules obtained to predict the output class for the observations in data file “testFinal.csv” and present your confusion matrix.

  actual
predicted 0 1
0
1

(c) [3 Points]

Use the rules obtained to predict the output class for the 10 observations in data file “newFinal.csv” and present your confusion matrix. [

x1 x2 x3 x4 x5 x6 x7 x8 x9 x10 class
0.36 0.30 0.68 0.38 0.02 0.61 0.53 0.52 0.35 0.78  
0.23 0.79 0.59 0.53 0.77 0.07 0.90 0.37 0.18 0.34  
0.80 0.96 0.35 0.69 0.19 0.59 0.85 0.55 0.75 0.68  
0.56 0.48 0.80 0.85 0.50 0.23 0.22 0.65 0.84 0.31  
0.75 0.39 0.47 0.02 0.19 0.23 0.99 0.03 0.65 0.87  
0.55 0.44 0.62 0.09 0.53 0.45 0.91 0.52 0.33 0.62  
0.20 0.70 0.24 0.81 0.22 0.01 0.82 0.67 0.40 0.46  
0.68 1.00 0.00 0.86 0.06 0.63 0.47 0.45 0.03 0.30  
0.08 0.49 0.97 0.08 0.68 0.82 0.89 0.82 0.47 0.96  
0.27 0.33 0.69 0.77 0.26 0.52 0.23 0.23 0.50 0.34  

MMIS 671: Fundamentals of Analytics and Business Intelligence

Solutions to Final Exam, Fall 2018

Name: __________________________________________

The work presented strictly reflects my individual efforts

Question 1.

a. Maximum profit attainable = $ …………………..[3 Points]

b. Number of gallons of each solvent used to produce each type of coolant [3 points]

Number of gallons used in: grade A grade B grade C
C1      
C2      

c. The company should be willing to pay at most $ ……………. for one additional gallon of grade A solvent (beyond its current availability of 60,000 gallons). [4 points]

Question 2.

Part a.

  Coefficient Estimate Significant?
Intercept    
x1    
x2    
x3    
x4    
x5    
x6    
x7    
x8    
x9    
x10    

Part b.

x1 x2 x3 x4 x5 x6 x7 x8 x9 x10 y
0.36 0.30 0.68 0.38 0.02 0.61 0.53 0.52 0.35 0.78  
0.23 0.79 0.59 0.53 0.77 0.07 0.90 0.37 0.18 0.34  
0.80 0.96 0.35 0.69 0.19 0.59 0.85 0.55 0.75 0.68  
0.56 0.48 0.80 0.85 0.50 0.23 0.22 0.65 0.84 0.31  
0.75 0.39 0.47 0.02 0.19 0.23 0.99 0.03 0.65 0.87  
0.55 0.44 0.62 0.09 0.53 0.45 0.91 0.52 0.33 0.62  
0.20 0.70 0.24 0.81 0.22 0.01 0.82 0.67 0.40 0.46  
0.68 1.00 0.00 0.86 0.06 0.63 0.47 0.45 0.03 0.30  
0.08 0.49 0.97 0.08 0.68 0.82 0.89 0.82 0.47 0.96  
0.27 0.33 0.69 0.77 0.26 0.52 0.23 0.23 0.50 0.34  

Question 3.

Part a. Rules obtained:

Rule 1.

Rule 2.

Rule 3.

….

….

 Part b. actual
predicted 0 1
0
1

Part c.

Predicted class

x1 x2 x3 x4 x5 x6 x7 x8 x9 x10 Predicted class
0.36 0.30 0.68 0.38 0.02 0.61 0.53 0.52 0.35 0.78  
0.23 0.79 0.59 0.53 0.77 0.07 0.90 0.37 0.18 0.34  
0.80 0.96 0.35 0.69 0.19 0.59 0.85 0.55 0.75 0.68  
0.56 0.48 0.80 0.85 0.50 0.23 0.22 0.65 0.84 0.31  
0.75 0.39 0.47 0.02 0.19 0.23 0.99 0.03 0.65 0.87  
0.55 0.44 0.62 0.09 0.53 0.45 0.91 0.52 0.33 0.62  
0.20 0.70 0.24 0.81 0.22 0.01 0.82 0.67 0.40 0.46  
0.68 1.00 0.00 0.86 0.06 0.63 0.47 0.45 0.03 0.30  
0.08 0.49 0.97 0.08 0.68 0.82 0.89 0.82 0.47 0.96  
0.27 0.33 0.69 0.77 0.26 0.52 0.23 0.23 0.50 0.34  

Explanations for Question 1.

Explanations for Question 2.

Explanations for Question 3.

8

Final Exam, MMIS 671, Fall 2018

Are you looking for a similar paper or any other quality academic essay? Then look no further. Our research paper writing service is what you require. Our team of experienced writers is on standby to deliver to you an original paper as per your specified instructions with zero plagiarism guaranteed. This is the perfect way you can prepare your own unique academic paper and score the grades you deserve.

Use the order calculator below and get ordering with idealtermpapers.com now! Contact our live support team for any assistance or inquiry.

Type of paper Academic level Subject area
Number of pages Paper urgency Cost per page:
 Total:

Purchase Guarantee

Why ORDER at IdealTermPapers.com?

  • Educated and experienced writers.
  • Quality, Professionalism and experience.
  • Original Content writing.
  • Best customer support.
  • Affordable Pricing on orders.
  • Thorough research.
  • Ontime delivery of finished work.
  • 100% plagiarism free papers.

Reasonable Prices

  • To get the best quality papers isn’t cheap so don’t trust extremely low prices.
  • We can’t claim that we have unreasonably low prices because low prices equal to low quality.
  • Our prices are good and they balance with the quality of our work.
  • We have a Moneyback guarantee.

Original and Quality work

  • Our writers are professionals and they write your paper from scratch and we don’t encourage copy pasting.
  • All writers are assessed and they have to pass our standards for them to work with us.
  • Plagiarism is an offence and it’s never tolerated in our company.

Native Writers plus Researchers

  • Our writers are qualified and excellent and will guarantee the best performance in your order.
  • Our team has writers who have master's and PhD qualifications who can handle any assignment
  • We have the best standards in essay writing.

We have been in business for over 7 syears

  • We have always served our customers from all over the world and they have continued to order with us.
  • We value our customers since they have trusted us to do their assignments.
  • We are competent in our writing gained from experience over the years
  • Our company has 24/7 Live Support.

You will get

  •  Custom Admission Essay written by competent professional English writers.
  •  Free revisions according to our revision policy if required
  •  Paper format:  275 words per page, Times New Roman font and size 12, doublespaced text and1 inch margin
  •  On time delivery and direct order download
  •  Privacy guaranteed

We can help you:

  •  acquire a comprehensive professional presentation.
  •  get a unique and remarkable content as per your instructions.
  •  Get an additional portion that can be included to your existing presentation;
  •  turn your work in to an eyecatching presentation with well communicated ideas.
  •  improve your presentation to acquire the best professional standards.