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Regression Hypothesis Test on Real Estate Data

Test the Hypothesis that homes located closer to the centre of the city, are higher in price than those homes located further away from the centre of the city.

-Perform a regression hypothesis test on the data
-Include a graph showing the results
-Include the results of your computations, using graphical and/or tabular methods of displaying data and results.

Price Bedrooms Size Pool Distance Twnship Garage Baths
263.1 4 2300 1 17 5 1 2
182.4 4 2100 0 19 4 0 2 Legend:
242.1 3 2300 0 12 3 0 2 X1: Selling price (in thousands)
213.6 2 2200 0 16 2 0 2.5 X2: Number of bedrooms
139.9 2 2100 0 28 1 0 1.5 X3: Size of the home in square feet
245.4 2 2100 1 12 1 1 2 X4: Pool (0=no, 1=yes)
327.2 6 2500 0 15 3 1 2 X5: Distance from the center
of the city in miles
271.8 2 2100 0 9 2 1 2.5 X6: Township
221.1 3 2300 1 18 1 0 1.5 X7: Garage attached (0=no, 1=yes)
266.6 4 2400 0 13 4 1 2 X8: Number of bathrooms
292.4 4 2100 0 14 3 1 2 105 homes sold
209 2 1700 0 8 4 1 1.5
270.8 6 2500 0 7 4 1 2
246.1 4 2100 0 18 3 1 2
194.4 2 2300 0 11 3 0 2
281.3 3 2100 0 16 2 1 2
172.7 4 2200 1 16 3 0 2
207.5 5 2300 1 21 4 0 2.5
198.9 3 2200 1 10 4 1 2
209.3 6 1900 1 15 4 1 2
252.3 4 2600 0 8 4 1 2
192.9 4 1900 1 14 2 1 2.5
209.3 5 2100 0 20 5 0 1.5
345.3 8 2600 0 9 4 1 2
326.3 6 2100 0 11 5 1 3
173.1 2 2200 1 21 5 1 1.5
187 2 1900 0 26 4 0 2
257.2 2 2100 0 9 4 1 2
233 3 2200 0 14 3 1 1.5
180.4 2 2000 0 11 5 0 2
234 2 1700 0 19 3 1 2
207.1 2 2000 0 11 5 1 2
247.7 5 2400 0 16 2 1 2
166.2 3 2000 1 16 2 1 2
177.1 2 1900 0 10 5 1 2
182.7 4 2000 1 14 4 0 2.5
216 4 2300 0 19 2 0 2
312.1 6 2600 0 7 5 1 2.5
199.8 3 2100 0 19 3 1 2
273.2 5 2200 0 16 2 1 3
206 3 2100 1 9 3 0 1.5
232.2 3 1900 1 16 1 1 1.5
198.3 4 2100 1 19 1 1 1.5
205.1 3 2000 1 20 4 0 2
175.6 4 2300 1 24 4 1 2
307.8 3 2400 1 21 2 1 3
269.2 5 2200 0 8 5 1 3
224.8 3 2200 0 17 1 1 2.5
171.6 3 2000 1 16 4 0 2
216.8 3 2200 0 15 1 1 2
192.6 6 2200 1 14 1 0 2
236.4 5 2200 0 20 3 1 2
172.4 3 2200 0 23 3 0 2
251.4 3 1900 0 12 2 1 2
246 6 2300 0 7 3 1 3
147.4 6 1700 1 12 1 0 2
176 4 2200 0 15 1 1 2
228.4 3 2300 0 17 5 1 1.5
166.5 3 1600 1 19 3 0 2.5
189.4 4 2200 0 24 1 1 2
312.1 7 2400 0 13 3 1 3
289.8 6 2000 0 21 3 1 3
269.9 5 2200 1 11 4 1 2.5
154.3 2 2000 0 13 2 0 2
222.1 2 2100 0 9 5 1 2
209.7 5 2200 1 13 2 1 2
190.9 3 2200 1 18 3 1 2
254.3 4 2500 1 15 3 1 2
207.5 3 2100 1 10 2 0 2
209.7 4 2200 1 19 2 1 2
294 2 2100 0 13 2 1 2.5
176.3 2 2000 1 17 3 0 2
294.3 7 2400 0 8 4 1 2
224 3 1900 1 6 1 1 2
125 2 1900 0 18 4 0 1.5
236.8 4 2600 1 17 5 1 2
164.1 4 2300 0 19 4 0 2
217.8 3 2500 0 12 3 0 2
192.2 2 2400 0 16 2 0 2.5
125.9 2 2400 0 28 1 0 1.5
220.9 2 2300 1 12 1 1 2
294.5 6 2700 0 15 3 1 2
244.6 2 2300 0 9 2 1 2.5
199 3 2500 1 18 1 0 1.5
240 4 2600 0 13 4 1 2
263.2 4 2300 0 14 3 1 2
188.1 2 1900 0 8 4 1 1.5
243.7 6 2700 0 7 4 1 2
221.5 4 2300 0 18 3 1 2
175 2 2500 0 11 3 0 2
253.2 3 2300 0 16 2 1 2
155.4 4 2400 1 16 3 0 2
186.7 5 2500 1 21 4 0 2.5
179 3 2400 1 10 4 1 2
188.3 6 2100 1 15 4 1 2
227.1 4 2900 0 8 4 1 2
173.6 4 2100 1 14 2 1 2.5
188.3 5 2300 0 20 5 0 1.5
310.8 8 2900 0 9 4 1 2
293.7 6 2400 0 11 5 1 3
179 3 2400 0 8 4 1 2
188.3 6 2100 1 14 2 1 2.5
227.1 4 2900 0 20 5 0 1.5
173.6 4 2100 0 9 4 1 2
188.3 5 2300 0 11 5 1 3

Solution Summary

The solution provides step-by-step method of performing a Regression Analysis and a Correlation Hypothesis Test in EXCEL. All the steps of hypothesis testing (formulation of null and alternate hypotheses, selection of significance level, choosing the appropriate test-statistic, decision rule, calculation of test-statistic and conclusion) have been explained and the Regression Analysis has been shown in details.

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