MATH 302 APUS Open a Second Office Mercer Human Resource Consulting Website Discussion

Content Type

User Generated

User

foevfp202

Subject

Mathematics

Course

MATH 302

School

American Public University System

Department

MATH

Description

A marketing company based out of New York City is doing well and is looking to expand internationally. The CEO and VP of Operations decide to enlist the help of a consulting firm that you work for, to help collect data and analyze market trends.

You work for Mercer Human Resources. The Mercer Human Resource Consulting website (www.mercer.com) lists prices of certain items in selected cities around the world. They also report an overall cost-of-living index for each city compared to the costs of hundreds of items in New York City (NYC). For example, London at 88.33 is 11.67% less expensive than NYC.

More specifically, if you choose to explore the website further you will find a lot of fun and interesting data. You can explore the website more on your own after the course concludes.

https://mobilityexchange.mercer.com/Insights/cost-of-living-rankings#rankings

This should be ¾ to 1 page, no more than 1 single-spaced page in length, using 12-point Times New Roman font. You do not need to do any calculations, but you do need to pick a city to open a second location at and justify your answer based upon the provided results of the Multiple Linear Regression.

The format of this assignment will be an Executive Summary. Think of this assignment as the first page of a much longer report, known as an Executive Summary, that essentially summarizes your findings briefly and at a high level. This needs to be written up neatly and professionally. This would be something you would present at a board meeting in a corporate environment. If you are unsure of an Executive Summary, this resource can help with an overview. What is an Executive Summary?

To help you make this decision here are some things to consider:

Based on the MLR output, what variable(s) is/are significant?
From the significant predictors, review the mean, median, min, max, Q1 and Q3 values?
- It might be a good idea to compare these values to what the New York value is for that variable. Remember New York is the baseline as that is where headquarters are located.
Based on the descriptive statistics, for the significant predictors, what city has the best potential?
- What city or cities fall are below the median?
- What city or cities are in the upper 3rd quartile?

Unformatted Attachment Preview

SUMMARY OUTPUT Regression Statistics Multiple R R Square Adjusted R Square Standard Error Observations 0.935824078 0.875766706 80.12% 8.30945321 17 ANOVA df Regression Residual Total SS 4867.380768 690.4701265 5557.850894 MS 811.2301279 69.04701265 Coefficients Standard Error 35.63950178 15.41876933 -0.003212852 0.003974813 0.299650003 0.076964051 16.59481787 6.713301249 2.912081706 1.98941146 -0.889805486 0.740190296 -2.527438053 6.484555358 t Stat 2.311436213 -0.808302603 3.89337619 2.47193106 1.463790555 -1.202130709 -0.389762738 6 10 16 Intercept Rent (in City Centre) Monthly Pubic Trans Pass Loaf of Bread Milk Bottle of Wine (mid-range) Coffee RESIDUAL OUTPUT Observation 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 Predicted Cost of Living Index 34.32607137 53.21656053 49.41436121 58.63611785 73.08449538 86.50256003 75.89216916 67.7257781 90.51996071 81.07358731 83.80564633 80.02510391 82.41624318 97.75654811 87.73993924 86.81668291 94.36817468 Residuals -2.586071368 -2.266560525 -3.964361215 4.42388215 5.105504624 -3.052560026 6.307830843 -0.975778105 -16.45996071 8.866412685 9.134353675 -8.37510391 3.483756815 2.243451893 3.040060757 1.11331709 -6.038174677 Standard Residuals -0.39366613 -0.345028417 -0.603477056 0.673427882 0.777188237 -0.464677621 0.960213003 -0.148538356 -2.50562653 1.349694525 1.390481989 -1.274904778 0.530316788 0.341510693 0.462774913 0.169475303 -0.919164446 F Significance F 11.74895331 0.00049963 P-value 0.043401141 0.437722785 0.002993072 0.032995588 0.173964311 0.257006081 0.704884259 City Mumbai Prague Warsaw Athens Rome Seoul Brussels Madrid Vancouver Paris Tokyo Berlin Amsterdam New York Sydney Dublin London Lower 95% 1.284342794 -0.012069287 0.128163411 1.636650533 -1.520603261 -2.539052244 -16.97592778 Upper 95% 69.99466077 0.005643584 0.471136595 31.55298521 7.344766672 0.759441271 11.92105168 Lower 95.0% Upper 95.0% 1.284342794 69.99466077 -0.012069287 0.005643584 0.128163411 0.471136595 1.636650533 31.55298521 -1.520603261 7.344766672 -2.539052244 0.759441271 -16.97592778 11.92105168 City Mumbai Prague Warsaw Athens Rome Seoul Brussels Madrid Vancouver Paris Tokyo Berlin Amsterdam New York Sydney Dublin London mean median min max Q1 Q3 New York Cost of Living Index 31.74 50.95 45.45 63.06 78.19 83.45 82.2 66.75 74.06 89.94 92.94 71.65 85.9 100 90.78 87.93 88.33 75.49 82.2 31.74 100 66.75 88.33 100 Rent (in City Centre) $1,642.68 $1,240.48 $1,060.06 $569.12 $2,354.10 $2,370.81 $1,734.75 $1,795.10 $2,937.27 $2,701.61 $2,197.03 $1,695.77 $2,823.28 $5,877.45 $3,777.72 $3,025.83 $4,069.99 $2,463.12 $2,354.10 $569.12 $5,877.45 $1,695.77 $2,937.27 $5,877.45 Monthly Pubic Trans Pass $7.66 $25.01 $30.09 $35.31 $41.20 $50.53 $57.68 $64.27 $74.28 $85.92 $88.77 $95.34 $105.93 $121.00 $124.55 $144.78 $173.81 $78.01 $74.28 $7.66 $173.81 $41.20 $105.93 $121.00 Loaf of Bread $0.41 $0.92 $0.69 $0.80 $1.38 $2.44 $1.66 $1.04 $2.28 $1.56 $1.77 $1.24 $1.33 $2.93 $1.94 $1.37 $1.23 $1.47 $1.37 $0.41 $2.93 $1.04 $1.77 $2.93 Milk $2.93 $3.14 $2.68 $5.35 $6.82 $7.90 $4.17 $3.63 $7.12 $4.68 $6.46 $3.52 $4.34 $3.98 $4.43 $4.31 $4.63 $4.71 $4.34 $2.68 $7.90 $3.63 $5.35 $3.98 Bottle of Wine (mid-range) $10.73 $5.46 $6.84 $8.24 $7.06 $17.57 $8.24 $5.89 $14.38 $8.24 $17.75 $5.89 $7.06 $15.00 $14.01 $14.12 $10.53 $10.41 $8.24 $5.46 $17.75 $7.06 $14.12 $15.00 Coffee $1.63 $2.17 $1.98 $2.88 $1.51 $1.79 $1.51 $1.58 $1.47 $1.51 $1.49 $1.71 $1.71 $0.84 $2.26 $2.06 $1.90 $1.76 $1.71 $0.84 $2.88 $1.51 $1.98 $0.84
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Explanation & Answer

Hey buddy, I have reviewed it and included additional info as the requirement was a single spaced document. So now it is complete and the answers are accurate. I am going to mark as final but you can always get back to me with what you need. Thank you.

Executive Summary
A marketing company which is currently headquartered at New York is seeking to expand
internationally and wants to identify a city to open a second location. Using Multiple Linear
regression, an analysis was performed to make the decision.
The two sig...