# Multiple choice: Confidence interval, multiple regression...

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1. Suppose that a 95% confidence interval for the population slope from a multiple regression is 0.14 to 1.33. How would we interpret this interval?

A) There is a 95% probability that the interval 0.14 to 1.33 includes the true mean.

B) 95% of the population slopes fall between 0.14 and 1.33.

C) 95% of the time the population slope falls between 0.14 and 1.33.

D) 95% of the y values fall between 0.14 and 1.33.

2. The adjusted coefficient of multiple determination is "adjusted for" what?

A) The number of predictors only.

B) The sample size only.

C) The number of predictors and the sample size.

D) None of the above

THE NEXT TWO QUESTIONS ARE BASED ON THE FOLLOWING INFORMATION:

A real estate appraiser is interested in determining the factors that determine the price of a house. She wants to run the following regression: where Y = price of the house in $1,000s, = number of bedrooms, = square footage of living space, and = number of miles from the beach. Taking a sample of 30 houses, the appraiser runs a multiple regression and get the following results: , = 103.2, = 2.13, = 0.062, = 4.17, , and (adjusted).

3. What price would we expect to pay on a 3 bedroom, 1,000 square foot house three miles from the beach?

A) $201,422

B) $177,243

C) $243,850

D) $229,198

4. What is the correct interpretation of the coefficient of determination ?

A) Approximately 47% of the time, sales price can be explained by these three variables.

B) Approximately 47% of the variation in sales prices can be determined by variation in these three variables.

C) The sales price equals 47% of these three variables.

D) Approximately 47% of the time, the sample values will lie on the regression line.

THE NEXT TWO QUESTIONS ARE BASED ON THE FOLLOWING INFORMATION:

A loan officer is interested in examining the determinants of the total dollar value of residential loans made during a month. She used to model the relationship, where Y is the total dollar value of residential loans in a month (in millions of dollars), is the number of loans, is the interest rate, and is the dollar value of expenditures of the bank on advertising (in advertising of dollars). Using data from the past 24 months, she obtained the following results: , = 3.2, = 0.03, = 0.062, = 0.17, = 0.46, and adjusted = 0.41.

5. How should she interpret the coefficient on ?

A) For every additional 1.3 percent increase in the interest rate, we would expect $1.0 million less in loans; total dollar values, with all other independent variables in the model held constant.

B) For every additional one percent increase in the interest rate, we would expect $1.3 million less in loans; total dollar values, with all other independent variables in the model held constant.

C) For every additional $1.0 million in loans, we would expect the interest rate to decrease by 1.3 percent; total dollar values, with all other independent variables in the model held constant.

D) For every additional $1.3 million in loans; total dollar values, with all other independent variables in the model held constant we would expect the interest rate to decrease by 1.0 percent.

6. What would we expect the total dollar value of loans to be in a month where there are 42 loans, the interest rate is 7.5%, and the bank spends $30,000 in advertising?

A) $6.442 million

B) $6.558 million

C) $6.288 million

D) $6.112 million

7. A goodness -of -fit-test is to be performed to see if consumers prefer any of four package designs (A, B, C, and D) more than the other three. If a random sample of 60 consumers is selected, what is the expected frequency for category A?

A) 0.25

B) 30

C) 15

D) 10

8. For a chi-square goodness- of- fit-test, the calculated chi-square value is 7.21. If the table chi-square value is 10.645, what is the appropriate decision for this test?

A) reject the null hypothesis

B) fail to reject the null hypothesis

C) accept the alternative hypothesis

D) impossible to determine from this information

9. Consider the following data set: 16, 16, 17, 18, 20, 21, 21, 22, 23, 24, 25, 27, 27, 27, 27, and 30. The rank assigned to the four observations of value 27 is:

A) 13

B) 13.5

C) 12

D) 12.5

10. The Wilcoxon rank sum test statistic T is approximately normally distributed whenever the sample sizes are larger than:

A) 10

B) 15

C) 20

D) 25

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