. Why is multicollinearity in a regression a difficulty to be resolved
. Why is m
d. For a 0.05 level of significance, should any variable be dropped from this model? Why or why not?
e. Interpret the value of R squared? How does this value from the adjusted R squared?
f. Predict the sales price of a 1134-square-foot home with a lot size of 15,400 square feet and 2 bedrooms.
PART III SPECIFIC KNOWLEDGE SHORT-ANSWER QUESTIONS.
Problem 7 Define Autocorrelation in the following terms: a. In what type of regression is it likely to occur?
b. What is bad about autocorrelation in a regression?
c. What method is used to determine if it exists? (Think of statistical test to be used)
d. If found in a regression how is it eliminated?
Problem 8 Define Multicollinearity in the following terms: a. In what type of regression is it likely to occur?
b. Why is multicollinearity in a regression a difficulty to be resolved?
c. How can multicollinearity be determined in a regression?. ulticollinearity in a regression a difficulty to be resolved
d. For a 0.05 level of significance, should any variable be dropped from this model? Why or why not?
e. Interpret the value of R squared? How does this value from the adjusted R squared?
f. Predict the sales price of a 1134-square-foot home with a lot size of 15,400 square feet and 2 bedrooms.
PART III SPECIFIC KNOWLEDGE SHORT-ANSWER QUESTIONS.
Problem 7 Define Autocorrelation in the following terms: a. In what type of regression is it likely to occur?
b. What is bad about autocorrelation in a regression?
c. What method is used to determine if it exists? (Think of statistical test to be used)
d. If found in a regression how is it eliminated?
Problem 8 Define Multicollinearity in the following terms: a. In what type of regression is it likely to occur?
b. Why is multicollinearity in a regression a difficulty to be resolved?
c. How can multicollinearity be
d. For a 0.05 level of significance, should any variable be dropped from this model? Why or why not?
e. Interpret the value of R squared? How does this value from the adjusted R squared?
f. Predict the sales price of a 1134-square-foot home with a lot size of 15,400 square feet and 2 bedrooms.
PART III SPECIFIC KNOWLEDGE SHORT-ANSWER QUESTIONS.
Problem 7 Define Autocorrelation in the following terms: a. In what type of regression is it likely to occur?
b. What is bad about autocorrelation in a regression?
c. What method is used to determine if it exists? (Think of statistical test to be used)
d. If found in a regression how is it eliminated?
Problem 8 Define Multicollinearity in the following terms: a. In what type of regression is it likely to occur?
b. Why is multicollinearity in a regression a difficulty to be resolved?
c. How can multicollinearity be determined in a regression?. ulticollinearity in a regression a difficulty to be resolved
d. For a 0.05 level of significance, should any variable be dropped from this model? Why or why not?
e. Interpret the value of R squared? How does this value from the adjusted R squared?
f. Predict the sales price of a 1134-square-foot home with a lot size of 15,400 square feet and 2 bedrooms.
PART III SPECIFIC KNOWLEDGE SHORT-ANSWER QUESTIONS.
Problem 7 Define Autocorrelation in the following terms: a. In what type of regression is it likely to occur?
b. What is bad about autocorrelation in a regression?
c. What method is used to determine if it exists? (Think of statistical test to be used)
d. If found in a regression how is it eliminated?
Problem 8 Define Multicollinearity in the following terms: a. In what type of regression is it likely to occur?
b. Why is multicollinearity in a regression a difficulty to be resolved?
c. How can multicollinearity be