Question

4. As a real estate analyst, you are requested by the manager to construct a simple linear regression for the relationship between the house value (x) and the upkeep spending (y).

(a) Write the simple linear regression equation below.

(b) What are b0 and b1?

(c) Interpret the meanings of b0 and b1.

(d) If the house value (x) is 150, what will the upkeep spending (y) be, using the simple linear regression model 4a?

(e) Draw the scatterplot showing the relationship between the house value (x) and the upkeep spending (y).

Value X	Upkeep Y
237.00	1412.08
153.08	797.20
184.86	872.48
222.06	1003.42
160.68	852.90
99.68	288.48
229.04	1288.46
101.78	423.08
257.86	1351.74
96.28	378.04
171.00	918.08
231.02	1627.24
228.32	1204.76
205.90	857.04
185.72	775.00
168.78	869.26
247.06	1396.00
155.54	711.50
224.20	1475.18
202.04	1413.32
153.04	849.14
232.18	1313.84
125.44	602.06
169.82	642.14
177.28	1038.80
162.82	697.00
120.44	324.34
191.10	965.10
158.78	920.14
178.50	950.90
272.20	1670.32
48.90	125.40
104.56	479.78
286.18	2010.64
83.72	368.36
86.20	425.60
133.58	626.90
212.86	1316.94
122.02	390.16
198.02	1090.84

Answer 1

we will solve it by using excel and the steps are

Enter the Data into excel

Click on Data tab

Click on Data Analysis

Select Regression

Select input Y Range as Range of dependent variable as upkeep spending (y).

Select Input X Range as Range of independent variable as house price

click on labels if your selecting data with labels

click on ok.

So this is the output of Regression in Excel.

SUMMARY OUTPUT
Regression Statistics
Multiple R	0.9430
R Square	0.8892
Adjusted R Square	0.8863
Standard Error	146.8973
Observations	40.0000
ANOVA
	df	SS	MS	F	Significance F
Regression	1.0000	6582759.6972	6582759.6972	305.0564	0.0000
Residual	38.0000	819995.5427	21578.8301
Total	39.0000	7402755.2399
	Coefficients	Standard Error	t Stat	P-value	Lower 95%	Upper 95%
Intercept	-348.3921	76.1410	-4.5756	0.0000	-502.5314	-194.2527
Value X	7.2583	0.4156	17.4659	0.0000	6.4170	8.0995

(a) Write the simple linear regression equation below

upkeep spending = -348.3921+7.2583House Value

b)

b0 = -348.3921

b1 = 7.2583

c)

b0 = -348.3921 this is the average upkeep spending when we consider Value X zero.

b1 = 7.2583 , if we increase House value by 1 , then there will be on an average increase in upkeep spending by 7.2583

d) If the house value (x) is 150, what will the upkeep spending (y) be, using the simple linear regression model 4a?

house value (x) is 150

upkeep spending = -348.3921+7.2583*150

upkeep spending = 740.3529

e) Draw the scatterplot showing the relationship between the house value (x) and the upkeep spending (y)

So there is positive linear relationship between upkeep spending and House price