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.

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^rd quartile?

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	$10.41	$1.76
median	82.2	$2,354.10	$74.28	$1.37	$4.34	$8.24	$1.71
min	31.74	$569.12	$7.66	$0.41	$2.68	$5.46	$0.84
max	100	$5,877.45	$173.81	$2.93	$7.90	$17.75	$2.88
Q1	66.75	$1,695.77	$41.20	$1.04	$3.63	$7.06	$1.51
Q3	88.33	$2,937.27	$105.93	$1.77	$5.35	$14.12	$1.98
New York	100	$5,877.45	$121.00	$2.93	$3.98	$15.00	$0.84

SUMMARY OUTPUT
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