Simple Regression Test Bank
CHAPTER 16
SIMPLE LINEAR REGRESSION
AND CORRELATION
SECTIONS 1 - 2
MULTIPLE CHOICE QUESTIONS
In the following multiple-choice questions, please circle the correct answer.
1. The regression line [pic] = 3 + 2x has been fitted to the data points (4, 8), (2, 5), and (1, 2). The sum of the squared residuals will be: a. 7 b. 15 c. 8 d. 22 ANSWER: d
2. If an estimated regression line has a y-intercept of 10 and a slope of 4, then when x = 2 the actual value of y is: a. 18 b. 15 c. 14 d. unknown ANSWER: d
3. Given the least squares regression line [pic]= 5 –2x: a. the relationship between x and y is positive b. the relationship between x and y is negative c. as x increases, so does y d. as x decreases, so does y ANSWER: b
4. A regression analysis between weight (y in pounds) and height (x in inches) resulted in the following least squares line: [pic]= 120 + 5x. This implies that if the height is increased by 1 inch, the weight, on average, is expected to: a. increase by 1 pound b. decrease by 1 pound c. increase by 5 pounds d. increase by 24 pounds ANSWER: c
5. A regression analysis between sales (in $1000) and advertising (in $100) resulted in the following least squares line: [pic] = 75 +6x. This implies that if advertising is $800, then the predicted amount of sales (in dollars) is: a. $4875 b. $123,000 c. $487,500 d. $12,300 ANSWER: b
6. A regression analysis between sales (in $1000) and advertising (in $) resulted in the following least squares line: [pic] = 80,000 + 5x. This implies that an: a. increase of $1 in advertising is expected, on average, to result in an increase of $5 in sales b. increase of $5 in advertising is expected, on average, to result in an increase of $5,000 in sales c. increase of $1 in advertising is expected, on average, to result in an increase of $80,005 in sales d.
SIMPLE LINEAR REGRESSION
AND CORRELATION
SECTIONS 1 - 2
MULTIPLE CHOICE QUESTIONS
In the following multiple-choice questions, please circle the correct answer.
1. The regression line [pic] = 3 + 2x has been fitted to the data points (4, 8), (2, 5), and (1, 2). The sum of the squared residuals will be: a. 7 b. 15 c. 8 d. 22 ANSWER: d
2. If an estimated regression line has a y-intercept of 10 and a slope of 4, then when x = 2 the actual value of y is: a. 18 b. 15 c. 14 d. unknown ANSWER: d
3. Given the least squares regression line [pic]= 5 –2x: a. the relationship between x and y is positive b. the relationship between x and y is negative c. as x increases, so does y d. as x decreases, so does y ANSWER: b
4. A regression analysis between weight (y in pounds) and height (x in inches) resulted in the following least squares line: [pic]= 120 + 5x. This implies that if the height is increased by 1 inch, the weight, on average, is expected to: a. increase by 1 pound b. decrease by 1 pound c. increase by 5 pounds d. increase by 24 pounds ANSWER: c
5. A regression analysis between sales (in $1000) and advertising (in $100) resulted in the following least squares line: [pic] = 75 +6x. This implies that if advertising is $800, then the predicted amount of sales (in dollars) is: a. $4875 b. $123,000 c. $487,500 d. $12,300 ANSWER: b
6. A regression analysis between sales (in $1000) and advertising (in $) resulted in the following least squares line: [pic] = 80,000 + 5x. This implies that an: a. increase of $1 in advertising is expected, on average, to result in an increase of $5 in sales b. increase of $5 in advertising is expected, on average, to result in an increase of $5,000 in sales c. increase of $1 in advertising is expected, on average, to result in an increase of $80,005 in sales d.