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REVIEW BOTH DOCUMENTS!!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 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

Assignment Guidance:

In the Excel document, you will find the 2018 data for 17 cities in the data set Cost of Living. Included are the 2018 cost of living index, cost of a 3-bedroom apartment (per month), price of monthly transportation pass, price of a mid-range bottle of wine, price of a loaf of bread (1 lb.), the price of a gallon of milk and price for a 12 oz. cup of black coffee. All prices are in U.S. dollars.
You use this information to run a Multiple Linear Regression to predict Cost of living, along with calculating various descriptive statistics. This is given in the Excel output (that is, the MLR has already been calculated. Your task is to interpret the data).

Based on this information, in which city should you open a second office in? You must justify your answer. If you want to recommend 2 or 3 different cities and rank them based on the data and your findings, this is fine as well.

Deliverable Requirements:

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?

Things to Consider:

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 Final MLR

SUMMARY OUTPUT

Regression Statistics

Multiple R
0.9358240783

R Square
0.8757667056

80.12%

Standard Error
8.3094532099

Observations
17

ANOVA

df
SS
MS
F
Significance F

Regression
6
4867.380767635
811.2301279392
11.748953312
0.0004996299

Residual
10
690.4701264826
69.0470126483

Total
16
5557.8508941176

Coefficients
Standard Error
t Stat
P-value
Lower 95%
Upper 95%
Lower 95.0%
Upper 95.0%

Intercept
35.6395017829
15.4187693276
2.3114362129
0.0434011406
1.2843427942
69.9946607717
1.2843427942
69.9946607717

Rent (in City Centre)
-0.0032128517
0.003974813
-0.8083026028
0.4377227847
-0.0120692871
0.0056435836
-0.0120692871
0.0056435836

Monthly Pubic Trans Pass
0.2996500033
0.0769640509
3.8933761896
0.0029930715
0.1281634113
0.4711365954
0.1281634113
0.4711365954

16.5948178712
6.7133012492
2.4719310597
0.0329955879
1.6366505328
31.5529852097
1.6366505328
31.5529852097

Milk
2.9120817057
1.9894114601
1.4637905552
0.1739643111
-1.5206032612
7.3447666725
-1.5206032612
7.3447666725

Bottle of Wine (mid-range)
-0.8898054861
0.7401902965
-1.2021307093
0.2570060814
-2.5390522435
0.7594412713
-2.5390522435
0.7594412713

Coffee
-2.5274380534
6.4845553577
-0.3897627384
0.7048842587
-16.9759277837
11.9210516769
-16.9759277837
11.9210516769

RESIDUAL OUTPUT

Observation
Predicted Cost of Living Index
Residuals
Standard Residuals
City

1
34.3260713681
-2.5860713681
-0.3936661298
Mumbai

2
53.2165605253
-2.2665605253
-0.3450284168
Prague

3
49.4143612149
-3.9643612149
-0.6034770563
Warsaw

4
58.6361178497
4.4238821503
0.6734278823
Athens

5
73.0844953758
5.1055046242
0.7771882365
Rome

6
86.5025600265
-3.0525600265
-0.4646776212
Seoul

7
75.8921691573
6.3078308427
0.9602130034
Brussels

8
67.7257781049
-0.9757781049
-0.1485383562

9
90.5199607051
-16.4599607051
-2.5056265297
Vancouver

10
81.0735873148
8.8664126852
1.3496945251
Paris

11
83.8056463253
9.1343536747
1.3904819889
Tokyo

12
80.02510391
-8.37510391
-1.2749047778
Berlin

13
82.4162431846
3.4837568154
0.5303167885
Amsterdam

14
97.7565481074
2.2434518926
0.3415106926
New York

15
87.7399392431
3.0400607569
0.4627749131
Sydney

16
86.8166829103
1.1133170897
0.1694753035
Dublin

17
94.3681746768
-6.0381746768
-0.9191644459
London

Data

City
Cost of Living Index
Rent (in City Centre)
Monthly Pubic Trans Pass
Milk
Bottle of Wine (mid-range)
Coffee

Mumbai
31.74
\$1,642.68
\$7.66
\$0.41
\$2.93
\$10.73
\$1.63

Prague
50.95
\$1,240.48
\$25.01
\$0.92
\$3.14
\$5.46
\$2.17

Warsaw
45.45
\$1,060.06
\$30.09
\$0.69
\$2.68
\$6.84
\$1.98

Athens
63.06
\$569.12
\$35.31
\$0.80
\$5.35
\$8.24
\$2.88

Rome
78.19
\$2,354.10
\$41.20
\$1.38
\$6.82
\$7.06
\$1.51

Seoul
83.45
\$2,370.81
\$50.53
\$2.44
\$7.90
\$17.57
\$1.79

Brussels
82.2
\$1,734.75
\$57.68
\$1.66
\$4.17
\$8.24
\$1.51

66.75
\$1,795.10
\$64.27
\$1.04
\$3.63
\$5.89
\$1.58

Vancouver
74.06
\$2,937.27
\$74.28
\$2.28
\$7.12
\$14.38
\$1.47

Paris
89.94
\$2,701.61
\$85.92
\$1.56
\$4.68

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