a) Test the null hypothesis that, in the presence of X1 and X3, X2 contributes no use- ful information for predicting Y . Please, provide: hypotheses, test statistic, p-value (or rejection region), and conclusion. Use α = 0.05. Could X2 be removed from the model? b)b) Test the null hypothesis that, in the presence of X3 = the number of square feet of living space, the two independent variables X1 = the number of bedrooms and X2 = the number of bathrooms are insignificant predictors of Y . Please, provide: hypotheses, test statistic, p-value (or rejection region), and conclusion. Use α = 0.05.

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a) Test the null hypothesis that, in the presence of X1 and X3, X2 contributes no use-
ful information for predicting Y . Please, provide: hypotheses, test statistic, p-value (or
rejection region), and conclusion. Use α = 0.05. Could X2 be removed from the model?

b)b) Test the null hypothesis that, in the presence of X3 = the number of square feet of living space,
the two independent variables X1 = the number of bedrooms and X2 = the number of bathrooms
are insignificant predictors of Y . Please, provide: hypotheses, test statistic, p-value (or
rejection region), and conclusion. Use α = 0.05.

 

6. The selling prices (Y), in thousands of dollars, of 24 apartments in Edmonton, Alberta
and data on the independent variables X₁, the number of bedrooms, X₂, the number of
bathrooms, and X3, the number of square feet of living space, are recorded in the following
table:
##
## 1
## 2
## 3
## 4
## 5
## 6
## 7
Price Bedrooms Bathrooms Square_feet
62.0
## 8
## 9
57.5
62.0
60.0
70.4
68.0
64.0
70.0
71.5
## 10
74.5
## 11 72.0
## 12
63.9
## 13
56.7
## 14 61.0
## 15
61.7
## 16
67.9
## 17
75.0
## 18 81.0
## 19 83.0
## 20 81.9
## 21 75.0
## 22 70.0
## 23 66.5
## 24 78.5
3
3
3
##
## Bedrooms
## Bathrooms
3
wo wo wo wo wo wo wo
3
3
3
3
3
3
3
3
3
4
4
4
4
4
4
4
4
4
4
4
2.0
2.0
2.0
2.0
2.0
2.0
2.0
2.0
2.0
2.0
1.5
1.5
1.5
2.0
2.0
2.0
2.0
2.5
2.5
2.5
2.5
2.5
2.5
2.5
1570
1500
1450
1466
1500
1708
1600
1617
1700
1768
1990
1470
1470
1580
2000
2000
2000
2050
2346
2415
2200
2150
2400
2085
modC-1m (Price "Bedrooms+Bathrooms+Square_feet);
anova (modC);
Df Sum Sq Mean Sq F value
1 316.36 316.36 10.6796
1 185.27 185.27 6.2540
## Square feet 1 263.16 263.16 8.8835
## Residuals 20 592.47
29.62
Transcribed Image Text:6. The selling prices (Y), in thousands of dollars, of 24 apartments in Edmonton, Alberta and data on the independent variables X₁, the number of bedrooms, X₂, the number of bathrooms, and X3, the number of square feet of living space, are recorded in the following table: ## ## 1 ## 2 ## 3 ## 4 ## 5 ## 6 ## 7 Price Bedrooms Bathrooms Square_feet 62.0 ## 8 ## 9 57.5 62.0 60.0 70.4 68.0 64.0 70.0 71.5 ## 10 74.5 ## 11 72.0 ## 12 63.9 ## 13 56.7 ## 14 61.0 ## 15 61.7 ## 16 67.9 ## 17 75.0 ## 18 81.0 ## 19 83.0 ## 20 81.9 ## 21 75.0 ## 22 70.0 ## 23 66.5 ## 24 78.5 3 3 3 ## ## Bedrooms ## Bathrooms 3 wo wo wo wo wo wo wo 3 3 3 3 3 3 3 3 3 4 4 4 4 4 4 4 4 4 4 4 2.0 2.0 2.0 2.0 2.0 2.0 2.0 2.0 2.0 2.0 1.5 1.5 1.5 2.0 2.0 2.0 2.0 2.5 2.5 2.5 2.5 2.5 2.5 2.5 1570 1500 1450 1466 1500 1708 1600 1617 1700 1768 1990 1470 1470 1580 2000 2000 2000 2050 2346 2415 2200 2150 2400 2085 modC-1m (Price "Bedrooms+Bathrooms+Square_feet); anova (modC); Df Sum Sq Mean Sq F value 1 316.36 316.36 10.6796 1 185.27 185.27 6.2540 ## Square feet 1 263.16 263.16 8.8835 ## Residuals 20 592.47 29.62
summary (modC);
Estimate Std. Error
38.54714637 8.336218482
t value
4.624057
-5.17269592 3.903698651 -1.325076
## Bathrooms
6.65774042 5.298320984 1.256576
## Square feet 0.01874226 0.006288257 2.980517
##
## (Intercept)
## Bedrooms
modR-1m (Price Square_feet);
anova (modR);
##
Df Sum Sq Mean Sq F value
## Square feet 1 688.25 688.25 22.633
## Residuals 22 669.00 30.41
summary (modR);
##
Estimate Std. Error t value
## (Intercept) 37.94708632 6.606324719 5.744054
## Square feet 0.01687907 0.003547935 4.757435
Transcribed Image Text:summary (modC); Estimate Std. Error 38.54714637 8.336218482 t value 4.624057 -5.17269592 3.903698651 -1.325076 ## Bathrooms 6.65774042 5.298320984 1.256576 ## Square feet 0.01874226 0.006288257 2.980517 ## ## (Intercept) ## Bedrooms modR-1m (Price Square_feet); anova (modR); ## Df Sum Sq Mean Sq F value ## Square feet 1 688.25 688.25 22.633 ## Residuals 22 669.00 30.41 summary (modR); ## Estimate Std. Error t value ## (Intercept) 37.94708632 6.606324719 5.744054 ## Square feet 0.01687907 0.003547935 4.757435
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