1. If an estimated regression line has a y-intercept of 10 and a slope of 4,...

 

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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 ŷ = 5 - 2x: 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: >= 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. 4. A regression analysis between sales (in $1,000) and advertising (in $1,000) resulted in the following least squares line: >= 80+ 5x. 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 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 ŷ = 5 - 2x: 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: >= 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. 4. A regression analysis between sales (in $1,000) and advertising (in $1,000) resulted in the following least squares line: >= 80+ 5x. 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

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Question 1 Estimated regression line can be represented using following equation Bo ... View the full answer