# Casestudy2:mortgageapprovaltimestudy | Statistics homework help

A major financial services company wishes to better understand its  mortgage approval process. In particular, the company is interested in  learning about the effects of credit history (good versus fair), the  size of the mortgage (<\$500,000 versus >\$500,000), and the region  of the United States (western versus eastern) on the amount of time it  takes to get a mortgage approved. The database of mortgages approved in  the last year is accessed, and a random sample of five approved  mortgages is selected for each of the eight combinations of the three  variables. The data are shown in the table ..

First, conduct an analysis using the following steps:

1. Use the data shown in the table to conduct a design of experiment  (DOE) in Microsoft Excel in order determine the nature and magnitude of  the effects of the three variables on mortgage approval times. What are  the key drivers of this process?
2. Determine the graphical display tool (e.g., Interaction Effects  Chart, Scatter Chart, et cetera) that you would use to present the  results of the DOE that you conducted in Question 1. Provide a rationale  for your response.
3. Assess the data sampling method. Our sample contained only five  mortgages per combination. Under what circumstances would it have been  appropriate to select a larger sample? Is a sample of five mortgages  adequate to access the relative magnitudes of the effects of the  variables? What sample size would you recommend? What could you learn  from a larger sample size? (Hint: Look back at chapter 2, 3, 5, and 6  for discussion of sampling.)
4. Provide other variable responses that might be of interest to  measure and study. (Hint: If you were getting a mortgage or a loan, what  are the two most important measures of the process you would have to go  through?)
5. Propose one overall recommendation to the financial services  company, based on the DOE, that could help reduce mortgage approval  times.

First, conduct an analysis using the following steps:

1. Use the data shown in the table to conduct a design of experiment  (DOE) in Microsoft Excel in order determine the nature and magnitude of  the effects of the three variables on mortgage approval times. What are  the key drivers of this process?
2. Determine the graphical display tool (e.g., Interaction Effects  Chart, Scatter Chart, et cetera) that you would use to present the  results of the DOE that you conducted in Question 1. Provide a rationale  for your response.
3. Assess the data sampling method. Our sample contained only five  mortgages per combination. Under what circumstances would it have been  appropriate to select a larger sample? Is a sample of five mortgages  adequate to access the relative magnitudes of the effects of the  variables? What sample size would you recommend? What could you learn  from a larger sample size? (Hint: Look back at chapter 2, 3, 5, and 6  for discussion of sampling.)
4. Provide other variable responses that might be of interest to  measure and study. (Hint: If you were getting a mortgage or a loan, what  are the two most important measures of the process you would have to go  through?)
5. Propose one overall recommendation to the financial services  company, based on the DOE, that could help reduce mortgage approval  times.

Second, create a PPT presentation to communicate the data analysis  you completed. Your presentation must follow these formatting  requirements:

• A PPT presentation with at least 10 slides that include the answers to questions 1 through 5.
• A reference slide which follows APA format. Check with your professor for any additional instructions.
• Formatting of the slides should be consistent and easy to read.
• Cover slide containing the title of the assignment, the student’s name, the professor’s name, the course title, and the date.
• Note: The cover slides and the reference slides are not included in the required assignment slides length.

The specific course learning outcome associated with this assignment is:

• Develop recommendations to improve business processes, using statistical tools and analysis.

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