Week 4 & 6 Regression Problems
Week 4 Problems
Complete the problems
422
The following data give the selling price, square footage, number of bedrooms, and age of houses that have sold in a neighborhood in the past 6 months. Develop three regression models to predict the selling price based upon each of the other factors individually. Which of these is best?
423 Use the data in Problem 422 and develop a regression model to predict selling price based on the square footage and number of bedrooms. Use this to predict the selling price of a 2,000squarefoot house with 3 bedrooms. Compare this model with the models in Problem 422. Should the number of bedrooms be included in the model? Why or why not?
424 Use the data in Problem 422 and develop a regression model to predict selling price based on the square footage, number of bedrooms, and age. Use this to predict the selling price of a 10yearold, 2,000squarefoot house with 3 bedrooms.
Week 6 Problems
61 Action Items
1.Read the Political Candidate Case.
2.Answer the following items about the case:
1.What is the Jim trying to optimize? Is he trying to maximize or minimize?
2.Write the objective function to support this analysis.
3.What inputs do you need to support your analysis?
4.Is there any extraneous data you have been given that you will not need?
5.What criteria has Jim given you to support the analysis?
3.Create a spreadsheet model that supports your analysis.
62 Action Items
1.Review the “Mexicana Wire Works” case study at the end of Chapter 7 in Quantitative Analysis.
2.Guidance:
1. Identify the one key item you are attempting to optimize (this becomes your SET TARGET CELL location
in Solver).
2. Identify the ten constraints associated with the problem.
3. Note that case facts like “defective product is stored separately until it can be reworked” is not pertinent,
whereas the April Orders chart is pertinent.
3.Complete the spreadsheet model and respond to the questions at the end of the case study.
63
Action Items
1.Review problem 737 in Chapter 7 of Quantitative Analysis.37) Bhavika Investments, a group of financial advisors and retirement planners, has been requested to provide advice on how to invest $200,000 for one of its clients. The client has stipulated that the money must be put into either a stock fund or a money market
fund, and the annual return should be at least $14,000. Other conditions related to risk have also been specified, and the following linear program was developed to help with this investment decision:
total investment is
$200,000
return must be at least
$14,000
at least $40,000 must be in money market fund where invested in stock fund
M = dollars invested in money market fund
S = dollars
S,M Ú 0
M Ú 40,000
0.10S + 0.05M Ú 14,000
S + M = 200,000
subject to
Minimize risk = 12S + 5M
The QM for Windows output is shown below.
(a) How much money should be invested in the money market fund and the stock fund? What is the total risk?
(b) What is the total return? What rate of return is this?
(c) Would the solution change if risk measure for each dollar in the stock fund were 14 instead of 12?
(d) For each additional dollar that is available, how much does the risk change?
(e) Would the solution change if the amount that must be invested in the money market fund were changed from $40,000 to $50,000?
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Week 4 & 6 Regression Problems was first posted on August 13, 2019 at 5:13 pm.
Week 4 & 6 Regression Problems was first posted on August 13, 2019 at 5:15 pm.
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