Determine the simple linear regression model for the rental and interpret the fitted model. Provide justifications to the conclusion you reach based on Figure 1. Determine and interpret the coefficient of determination, ². Ben and Helen are considering to rent a unit of a condominium. They are trying to decide between two condominium units, one with 1000 square metres for a monthly rental of RM1500 and the other with 1200 square metres for RM1800. Which condominium unit would you recommend to them?
Determine the simple linear regression model for the rental and interpret the fitted model. Provide justifications to the conclusion you reach based on Figure 1. Determine and interpret the coefficient of determination, ². Ben and Helen are considering to rent a unit of a condominium. They are trying to decide between two condominium units, one with 1000 square metres for a monthly rental of RM1500 and the other with 1200 square metres for RM1800. Which condominium unit would you recommend to them?
MATLAB: An Introduction with Applications
6th Edition
ISBN:9781119256830
Author:Amos Gilat
Publisher:Amos Gilat
Chapter1: Starting With Matlab
Section: Chapter Questions
Problem 1P
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Transcribed Image Text:Determine the simple linear regression model for the rental and interpret the fitted
model. Provide justifications to the conclusion you reach based on Figure 1. Determine
and interpret the coefficient of determination, ².
Ben and Helen are considering to rent a unit of a condominium. They are trying to
decide between two condominium units, one with 1000 square metres for a monthly
rental of RM1500 and the other with 1200 square metres for RM1800. Which
condominium unit would you recommend to them?

Transcribed Image Text:An agent from a property rental company would like to predict the monthly rental for
condominium based on the size as defined in square metres. A sample of 25
condominiums was selected. Data is generated and the summary of outputs are shown
in Table 1 and Figure 1.
ANOVA
df
SS
MS
F
59.914
Significance
F
7.52E-08
Regression
Residual
1 2268776.545 2268777
23 870949.4547 37867.37
Total
24
3139726
Standard
Error
161.00427
t Stat
P-value
Coefficients
177.1208
1.0651
1.100
Intercept
Size
0.282
0.13760
7.740 7.52E-08
Table 1
Size Residual Plot
500
400
300
200
100
0
-100
-200
◆ 1000
-300
-400
-500
Residuals
500
Size
Figure 1
+500
2000
2500
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