A real estate builder wishes to determine how house size (House) is influenced b
ID: 3262347 • Letter: A
Question
A real estate builder wishes to determine how house size (House) is influenced by family income (Income), family size (Size), and education of the head of household (School). House size is measured in hundreds of square feet, income is measured in thousands of dollars, and education is in years. The builder randomly selected 50 families and ran the multiple regression. Microsoft Excel output is provided below:
Question 1. Which of the following values for the level of significance is the smallest, for which all explanatory variables are significant individually?
a.) 0.025 b.) 0.05, c.) 0.15 d.) 0.01
Question 2. Which of the following values for the level of significance is the smallest, for which at least two explanatory variables are significant individually?
a.) 0.01 b.) 0.15, c.) 0.05 d.) 0.025
Question 3. Which of the following values for the level of significance is the smallest, for which the regression model as a whole is significant?
a.) 0.001 b.) 0.01, c.) 0.00005 d.) 0.05
SUMMARY OUTPUT Regression Statistics Multiple R 0.865 R Square 0.748 Adjusted R Square 0.726 Standard Error 5.195 Observations 50Explanation / Answer
If the p-value for a value is less than level of signficance then variable is significant to the model.
The p-value for income variable is 0.0003
The p-value for size variable is 0.0001
The p-value for school variable is 0.1383
(a)
Since all these values are less than 0.15 so these all are signficant to model at 0.15 level of signficance.
Answer : option c) 0.15
Question 2:
Since variables income and size have p-value less than 0.01 so answer is option a): 0.01.
Question 3:
The F value for the model is 0.0000.
Since this p-value is less than 0.00005 so model is signficant at 0.00005 level of signficance.
Answer: c) 0.00005
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