The real estate profession is interested in understanding how the rent (??1) and the cost to hold a onebedroom apartment (?2) affect the price of the onebedroom apartment (y). He fits the model as:
? = ?0 + ?1?1 + ?2?2
Coefficients: 

Estimate 
Std. Error 
t value 
Pr ( >t) 

(Intercept) 
176.27867 
23.36940 
7.543 
<1.23e9 *** 
rent 
0.55701 
0.07114 
7.830 
<4.58e10 *** 
cost 
0.35332 
0.10118 
3.492 
< 0.00105 *** 
Signif. codes: 0 ‘***’ 0 ‘**’ 0.01‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1 

Residual standard error: 2.559 on 47 degrees of freedom 

Multiple Rsquared: 0.9994 Adjusted Rsquared: 0.9994 

Fstatistic: 4.16e04 on 2 and 47 DF pvalue: < 2.2e16 
a)
t value for Intercept = 176.27867/ 23.36940 = 7.543
t value for rent = 0.55701/ 0.07114 = 7.830
t value for cost = 0.35332/ 0.10118 = 3.492
b)
For Rent:
As pvalue < 0.05, we reject the null hypothesis.
It is significant. We will not remove rent.
For cost:
As pvalue < 0.05, we reject the null hypothesis.
It is significant. We will not remove cost.
c)
Pvalue for overall model = 2.2e16
As pvalue < 0.05, we reject the null hypothesis.
The overall model is significant.
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