b. What is your regression line written in the form ŷ = a+bx? (Round a and b to 3 decimal places pleasel) b. Use your regression equation above to predict the height of a building with 70 stories: (Please enter a whole number) C.Compute the coefficient of determination (write It as a decimal here). d. Determine the percentage of the variation in the observed values of the response variable, height, explained by the regression with the explanatory variable, stories. 96 e. The predictor variable,x, is and the response variable is 1. How would you interpret the slope-of the regression line in words? For every 1 foot increase in height, the number of stories increases by about 11.76 stories on average. O For every 1 story increase in the number of stories a building has, the height increases by about 11.76 feet on average. OA1-story building will be 11,76 feet high O For each 102.43 stories increase in the number of stories, the height will increase by 1 foot, on average. OFor every 1 story increase in the number of stores a bulding has, the height increases by about 102.43 feet on average. RWould it be valid to use this regression line to estimate the average height of a building with 10 stories?

b. What is your regression line written in the form ŷ = a+bx? (Round a and b to 3 decimal places pleasel) b. Use your regression equation above to predict the height of a building with 70 stories: (Please enter a whole number) C.Compute the coefficient of determination (write It as a decimal here). d. Determine the percentage of the variation in the observed values of the response variable, height, explained by the regression with the explanatory variable, stories. 96 e. The predictor variable,x, is and the response variable is 1. How would you interpret the slope-of the regression line in words? For every 1 foot increase in height, the number of stories increases by about 11.76 stories on average. O For every 1 story increase in the number of stories a building has, the height increases by about 11.76 feet on average. OA1-story building will be 11,76 feet high O For each 102.43 stories increase in the number of stories, the height will increase by 1 foot, on average. OFor every 1 story increase in the number of stores a bulding has, the height increases by about 102.43 feet on average. RWould it be valid to use this regression line to estimate the average height of a building with 10 stories?

MATLAB: An Introduction with Applications

6th Edition

ISBN:9781119256830

Author:Amos Gilat

Publisher:Amos Gilat

Chapter1: Starting With Matlab

Section: Chapter Questions

Problem 1P

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Please solve what’s not filled in.
Choose the correct answer of each number. 1. An analyst hired by the multinational company to study the sales data of its more than 75 stores worldwide. Used regression analysis to predict $ sales (y) by using $ advertising (x1) and $ salary of sales representatives (x2) across all the branches. You obtained the following regression function: y = 7800 + 8.5x1-1.6x2. If the advertising budgets of one of the branches of the corporation is now $45,000 (which is 10% more than before) and the salary of sales representatives is now $8,500 (which is 20% less than before), then the predicted sales before in that branch is a. $417,750 b. $341,250 c. $376,700 d. $335,6502. An analyst hired by the multinational company to study the sales data of its more than 75 stores worldwide. Used regression analysis to predict $ sales (y) by using $ advertising (x1) and $ salary of sales representatives (x2) across all the branches. You obtained the following regression function: y = 7800 + 8.5x1-1.6x2. If…
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Using the weights (lb) 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. The site to your captio V.UVITU. D. The slope is -0.00749 and the y-intercept is 58.9. c. What is the predictor variable? ... OA. The predictor variable is highway fuel consumption, which is represented by x. OB. The predictor variable is highway fuel consumption, which is represented by y. C. The predictor variable is weight, which is represented by x. OD. The predictor variable is weight, which is represented by y. d. Assuming that there is a significant linear correlation between weight and highway fuel consumption, what is the best predicted value for a car that weighs 2994 lb? The best predicted value of highway fuel consumption of a car that weighs 2994 lb is (Round to one decimal place as needed.) mi/gal.
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