Regression Hypothesis Test on Real Estate Data
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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
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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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