. Why is multicollinearity in a regression a difficulty to be resolved

Pages: 3 (465 words) Published: October 11, 2013
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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?

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?

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...