A data set consists of these points: (2, 4), (4, 7), (5, 12). Malinda found the regression equation to be y = 2.5x- 1.5. Is she correct? O A. No. Both a and b are incorrect. B. No. The value for bis incorrect. O C. No. The value for a is incorrect. D. Yes. This is the correct equation.
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- K a. Using the pairs of values for all 10 points, find the equation of the regression line. b. After removing the point with coordinates (2,2), use the pairs of values for the remaining 9 points and find the equation of the regression line. c. Compare the results from parts (a) and (b). FICEERD a. What is the equation of the regression line for all 10 points? y=+x (Round to three decimal places as needed.) X 10- 8- 6- 4 2- 10- 0 2 4 6 8 10How do I go about these two questions followin this asnwer above: B) Ater removing the point with coordinates (2,9), use the pairs of values for the remaining 9 points and find the equation of the regression line. c. Compare the results from parts (a) and (b).Suppose Ms. Carr is interested in the relationship between her students' 9th grade math final exam scores and the number of hours they spent studying during the year. She collects information for 15 ninth grade students and uses it to obtain the regression equation, where ?x is the number of hours spent studying during the year and ?̂ is the predicted final exam score. ?̂ =1.48?+75.64 The scatter plot displays her results. What is the predicted ?̂ value when a student spends 13 hours studying? Round your answer to one decimal place. Select the correct interpretation. The above predicted value of ?̂ is the predicted final math test score if a student studies 13 hours during the year. the predicted score of 13 out of 15 students. what any student will score on the final exam if they study at least 13 hours. the math final test score that 13 students beat.
- ♦️♦️❎♦️✅✅✅♦️♦️Please help ))()()The table shows the amounts of crude oil (in thousands of barrels per day) produced by a certain country and the amounts of crude oil (in thousands of barrels per day) imported by the same country for seven years. The equation of the regression line is y =-1.364x+17,178.20. Complete parts (a) and (b) below. Produced, x Imported, y 5,744 5,554 5,439 5,188 5,136 5,067 D 9,132 9,677 10,017 10,193 10,149 10,075 5,756 9,328 (a) Find the coefficient of determination and interpret the result. (Round to three decimal places as needed.)
- The arm span and foot length were both measured (in centimeters) for each of 20 students in a biology class. The computer output displays the regression analysis. Which of the following is the best interpretation of the coefficient of determination r2? About 37% of the variation in arm span is accounted for by the linear relationship formed with the foot length. About 65% of the variation in foot length is accounted for by the linear relationship formed with the arm span. About 63% of the variation in arm span is accounted for by the linear relationship formed with the foot length. About 63% of the variation in foot length is accounted for by the linear relationship formed with the arm span.Consider the following regression equation: y = -3.9 + 7.2x What does 7.2 depict in the regression equation above? a) The direction of the line. b) The y-intercept. c) The point where x = 0. d) The y when x = 7.2.Use the given data set to answer parts (a) and (b). a. Find the regression equation for the data points. X 5 b. Graph the regression equation and the data points. y -1 10 -10 y B. 10 -10- C. a. Find the regression equation for the data points. ŷ-0 (Use integers or decimals for any numbers in the expression. Round to two decimal places as needed.) b. Graph the regression equation and the data points. O A. 10 T -10- 1 2 -1 3 327 D. -10 4 y 4 28 0
- The table shows the amounts of crude oil (in thousands of barrels per day) produced by a certain country and the amounts of crude oil (in thousands of barrels per day) imported by the same country for seven years. The equation of the regression line is y = - 1.269x + 16,635.60. Complete parts (a) and (b) below. Produced, x Imported, y 5,718 5,612 5,409 5,228 5,128 5,006 O 9,106 9,631 10,000 10,140 10,133 10,059 5,759 9,318 (a) Find the coefficient of determination and interpret the result. (Round to three decimal places as needed.)a. Using the pairs of values for all 10 points, find the equation of the regression line. b. After removing the point with coordinates (2,3), use the pairs of values for the remaining 9 points and find the equation of the regression line. c. Compare the results from parts (a) and (b).Using the weights (Ib) and highway fuel consumption amounts (mi/gal) of the 48 cars listed in the accompanying data set, one gets this regression equation: y = 58 9-0.00749x, where x represents weight Complete parts (a) through (d). Click the icon to view the car data. 東 b. What are the specific values of the slope and y-intercept of the regression line? O A. The slope is 58.9 and the y-intercept is 0.007499. B. The slope is -0.00749 and the y-intercept is 58.9. O C. The slope is 58.9 and the y-intercept is -0.00749. O D. The slope is 0.00749 and the y-intercept is 58.9. c. What is the predictor variable? O A. The predictor variable is highway fuel consumption, which is represented by x. B. The predictor variable is weight, which is represented by x. O C. The predictor variable is weight, which is represented by y O D. The predictor variable is highway fuel consumption, which is represented by y. d. Assuming that there is a significant linear correlation between weight and highway fuel…