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Regression analysis on Real estate data

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Using the attached numerical data I want to (1) formulate a hypothesis which can be tested with linear regression analysis. (2) Formulate a hypothesis statement regarding the issue. (3) Perform a regression hypothesis test on the data. (4) Interpret the results of your regression hypothesis test. (5) And have to include raw data tables and the results of computations in the paper, using both graphical and 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
242.1 3 2300 0 12 3 0 2
213.6 2 2200 0 16 2 0 2.5
139.9 2 2100 0 28 1 0 1.5
245.4 2 2100 1 12 1 1 2
327.2 6 2500 0 15 3 1 2
271.8 2 2100 0 9 2 1 2.5
221.1 3 2300 1 18 1 0 1.5
266.6 4 2400 0 13 4 1 2
292.4 4 2100 0 14 3 1 2
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 for the calculation of regression model for real estate data set . Formula for the calculation and Interpretations of the results are also included.

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