The following estimated regression equation has been proposed to predict sales at a fast food outlet.ŷ = 51 - 5x₁ + 25x₂ + 12x31where157°FCloudyf1x₂ = population within 1 mile (in 1,000s)X2QX₁Predict sales (in dollars) for the store with the competitor's previous day's sale of $6,000, a population of 29,000 within 1 mile, and five radio advertisements.$695111?1x3 == 1 if radio advertising was used; 0 otherwiseý = estimated sales (in $1,000s)Need Help? Read Itcompetitor's previous day's sales (in $1,000s)f22Jf3#3BLOWEEf4*****$4Rf5040do5f64-T6f72♫+&YREfg7ⒸDDI*hpfgUDII8f109finÖ01f12insert2SUPERprt sc[

The estimated regression equation that has been proposed to predict sales at a fast food outlet is…

Answered: The following estimated regression…

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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A sports-equipment researcher was interested in the relationship between the speed of a golf club (in feet per second) and the distance a golf ball travels (in yards). Information was collected on several golfers and was used to obtain the regression equation ŷ = 2x - 106, where x represents the club speed and ŷ is the predicted distance. Which statement best describes the meaning of the slope of the regression line? For each increase in distance by 1 yard, the predicted club speed increases by 2 ft/sec. For each increase in distance by 1 yard, the predicted club speed decreases by 106 ft/sec. For each increase in club speed by 1 ft/sec, the predicted distance increases by 2 yards. For each increase in club speed by 1 ft/sec, the predicted distance decreases by 106 yards.
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.
The following data show the brand, price ($), and the overall score for six stereo headphones that were tested by a certain magazine. The overall score is based on sound quality and effectiveness of ambient noise reduction. Scores range from 0 (lowest) to 100 (highest). The estimated regression equation for these data is ŷ = 22.391 + 0.326x, where x = price ($) and y = overall score. Brand Price ($) Score A 180 76 B 150 71 C 95 63 D 70 56 E 70 40 F 35 24 #1) Compute SST, SSR, and SSE. (Round your answers to three decimal places.) SST = SSR = SSE = #2) Compute the coefficient of determination r2.(Round your answer to three decimal places.) r2 = #2a) Comment on the goodness of fit. (For purposes of this exercise, consider a proportion large if it is at least 0.55.) A) The least squares line provided a good fit as a small proportion of the variability in y has been explained by the least squares line. B) The least squares line provided a good fit as a large…
A pediatrician wants to determine the relation that exists between a child's height (x) and head circumference (y). She randomly selects 11 children from her practice and measures their height and head circumference in inches. She finds that the correlation is 0.694, and the regression equation is y = 0.294x + 2.02. What proportion of the variation in head circumference can be explained by the variation in the values of height? Round your answer to three decimal places. %
A. Develop an estimated regression equation that can be used to predict the price of the stock based on the number of shares of company's stocks sold and the volume of exchange. B. Interpret the coefficients of the estimated regression equation that you found in Part a. C. If in a given day, the number of shares of the company that were sold was 94,500 and the volume of exchange on the New York Stock Exchange was 16 million, what would you expect the price of the stock to be?
In 2012, the CDC published data on the average weight of American female children by year. Using ages 1−7 of this data, researchers made a linear regression with age in years as the x variable and weight in pounds as the y variable. The equation of the line of best fit is yˆ=5.78x+17.56. According to the line of best fit, what would you predict the weight would be for a 14-year-old female? Is it reasonable to use this line of best fit to make this prediction?

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