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:

You do not need to make 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.

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 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 3^rdquartile?

City Cost of Living Index; Rent (in City Centre); Monthly Pubic Trans Pass; Loaf of Bread; 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

Madrid 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 $8.24 $1.51

Tokyo 92.94 $2,197.03 $88.77 $1.77 $6.46 $17.75 $1.49

Berlin 71.65 $1,695.77 $95.34 $1.24 $3.52 $5.89 $1.71

Amsterdam 85.9 $2,823.28 $105.93 $1.33 $4.34 $7.06 $1.71

New York 100 $5,877.45 $121.00 $2.93 $3.98 $15.00 $0.84

Sydney 90.78 $3,777.72 $124.55 $1.94 $4.43 $14.01 $2.26

Dublin 87.93 $3,025.83 $144.78 $1.37 $4.31 $14.12 $2.06

London 88.33 $4,069.99 $173.81 $1.23 $4.63 $10.53 $1.90

mean 75.49 $2,463.12 $78.01 $1.47 $4.71

median 82.2 $2,354.10 $74.28 $1.37 $4.34

min 31.74 $569.12 $7.66 $0.41 $2.68

max 100 $5,877.45 $173.81 $2.93 $7.90

Q1 66.75 $1,695.77 $41.20 $1.04 $3.63

Q3 88.33 $2,937.27 $105.93 $1.77 $5.35

New York 100 $5,877.45 $121.00 $2.93 $3.98

Regression Statistics

Multiple R 0.935824078

R Square 0.875766706

Adjusted R Square 80.12%

Standard Error 8.30945321

Observations 17

ANOVA

df; SS; MS; F; Significance F

Regression; 6; 4867.380768; 811.2301279; 11.74895331; 0.00049963

Residual; 10; 690.4701265; 69.04701265

Total; 16; 5557.850894

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

Intercept; 35.63950178; 15.41876933; 2.311436213; 0.043401141; 1.284342794; 69.99466077; 1.284342794; 69.99466077

Rent (in City Centre); -0.003212852; 0.003974813; -0.808302603; 0.437722785; -0.012069287; 0.005643584; -0.012069287; 0.005643584

Monthly Pubic Trans Pass; 0.299650003; 0.076964051; 3.89337619; 0.002993072; 0.128163411; 0.471136595; 0.128163411; 0.471136595

Loaf of Bread; 16.59481787; 6.713301249; 2.47193106; 0.032995588; 1.636650533; 31.55298521; 1.636650533; 31.55298521

Milk; 2.912081706; 1.98941146; 1.463790555; 0.173964311; -1.520603261; 7.344766672; -1.520603261; 7.344766672

Bottle of Wine (mid-range); -0.889805486; 0.740190296; -1.202130709; 0.257006081; -2.539052244; 0.759441271; -2.539052244; 0.759441271

Coffee; -2.527438053; 6.484555358; -0.389762738; 0.704884259; -16.97592778; 11.92105168; -16.97592778; 11.92105168

RESIDUAL OUTPUT

Observation Predicted Cost of Living Index Residuals Standard Residuals City

1) 34.32607137; -2.586071368; -0.39366613; Mumbai

2) 53.21656053; -2.266560525; -0.345028417 Prague

3) 49.41436121; -3.964361215; -0.603477056 Warsaw

4) 58.63611785; 4.42388215; 0.673427882 Athens

5) 73.08449538; 5.105504624; 0.777188237 Rome

6) 86.50256003; -3.052560026; -0.464677621 Seoul

7) 75.89216916; 6.307830843; 0.960213003 Brussels

8) 67.7257781; -0.975778105; -0.148538356 Madrid

9) 90.51996071; -16.45996071; -2.50562653 Vancouver

10) 81.07358731; 8.866412685; 1.349694525 Paris

11) 83.80564633; 9.134353675; 1.390481989 Tokyo

12) 80.02510391; -8.37510391; -1.274904778 Berlin

13) 82.41624318; 3.483756815; 0.530316788 Amsterdam

14) 97.75654811; 2.243451893; 0.341510693 New York

15) 87.73993924; 3.040060757; 0.462774913 Sydney

16) 86.81668291; 1.11331709; 0.169475303 Dublin

17) 94.36817468; -6.038174677; -0.919164446 London