PLEASE ANSWER ALL 5. 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.
Given the least squares regression line hat(y)=5-2x+ errors:
a. the relationship between x and y is positive.
b. the relationship between x and y is negative.
c. as x decreases, so does y.
d. None of these choices.
A regression analysis between weight ( y in pounds) and height ( x in inches) resulted in
the following least squares line: hat(y)=120+5x+ errors. 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.
A regression analysis between sales (in $1,000 ) and advertising (in $1,000 ) resulted in
the following least squares line: hat(y)=80+5x+ errors. This implies that:
a. as advertising increases by $1,000, sales increases by $5,000.
b. as advertising increases by $1,000, sales increases by $80,000.
c. as advertising increases by $5, sales increases by $80.
d. None of these choices.
The residual is defined as the difference between:
a. the actual value of y and the estimated value of y
b. the actual value of x and the estimated value of x
c. the actual value of y and the estimated value of x
d. the actual value of x and the estimated value of y
1. 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.
2. Given the least squares regression line y = 5 -- 2x + errors: a. the relationship between x and y is positive. b. the relationship between x and y is negative c. as x decreases, so does y. d. None of these choices.
3. A regression analysis between weight (y in pounds) and height (x in inches) resulted in the following least squares line: y = 120 + 5x + errors. 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 I pound. C. increase by 5 pounds. d. increase by 24 pounds.
4. A regression analysis between sales (in $1,000) and advertising (in $1,000) resulted in the following least squares line: y = 80 + 5x + errors. This implies that: a. as advertising increases by $1,000, sales increases by $5,000 b.as advertising increases by $1,000, sales increases by $80,000. c. as advertising increases by $5, sales increases by $80 d. None of these choices.
5. The residual is defined as the difference between: a. the actual value of y and the estimated value of y b. the actual value of x and the estimated value of x c. the actual value of y and the estimated value of x d. the actual value of x and the estimated value of y
