Management proposed the following regression model to predict sales at a fast-food outlet.y = Bot Bixit ByxtBox tewhereX₁ = number of competitors within one mileX₂= population within one mile (1000s)1 if drive-up window present(0 otherwisey sales ($1000s)X₂ =The following estimated regression equation was developed after 20 outlets were surveyed.ŷ= 10.7-4.61 +6.722 +15.7x3a. What is the expected amount of sales attributable to the drive-up window?$b. Predict sales for a store with two competitors, a population of 9,000 within one mile, and no drive-up window.Estimate of sales = $1c. Predict sales for a store with one competitor, a population of 3,000 within one mile, and a drive-up window.Estimate of sales $

Given data: The multiple regression equation is: ŷ =10.7–4.6x1+6.7x2+15.7x3 where x1=number of…

Answered: Management proposed the following…

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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The following data show the brand, price ($), and the overall score for six stereo headphones that were tested by a certain magazine. The overall score is based on sound quality and effectiveness of ambient noise reduction. Scores range from 0 (lowest) to 100 (highest). The estimated regression equation for these data is ŷ = 22.458 + 0.325x, where x = price ($) and y = overall score. Brand Price ($) Score A 180 78 B 150 69 C 95 63 D 70 54 E 70 40 F 35 26 (a) Compute SST (Total Sum of Squares), SSR (Regression Sum of Squares), and SSE (Error Sum of Squares). (Round your answers to three decimal places.) SST=SSR=SSE= (b) Compute the coefficient of determination r2. (Round your answer to three decimal places.) r2 = Comment on the goodness of fit. (For purposes of this exercise, consider a proportion large if it is at least 0.55.) The least squares line provided a good fit as a small proportion of the variability in y has been explained by the least squares…
The estimated regression model is given : Consumption = 49.13 + 0.85 Income + error Consumption is dependent variable ; Income ( weekly) - family Income Let's say a family income earns $ 100 more per week . How to affect the consumption level? Choose one right answer A. For every 100 $ a family earns more per week in this case the consumption will grow on average and expected of 85 $ worth. B. For every 100 $ a family earns more per week in this case the consumption will fall on average and expected of 49.14 $ worth.
There is a linear relationship between the number of chirps made by the stiped ground cricket and the air temperature. It was determined that the linear regression model is: y = 25.2 + 3.3x where x is the number of chirps per minute and y is the estimated temperature in degrees Fahrenheit. What is the predicted number of chirps made when the temperature is 60 degrees Fahrenheit? Round to the nearest integer. Do not include units.
Mary used a sample of 68 large U.S. cities to estimate the relationship between Crime (annual property crimes per 100,000 persons) and Income (median annual income per capita, in dollars). Her estimated regression equation was Crime = 428 + 0.050 Income. If Income decreases by 500, we would expect that Crime will Group of answer choices remain unchanged. decrease by 25. increase by 500. decrease by 50.
Tire pressure (psi) and mileage (mpg) were recorded for a random sample of seven cars of thesame make and model. The extended data table (left) and fit model report (right) are based on aquadratic model. Calculate R2. Describe what this value means in the context of the problem.
The scatterplot below shows the relationship between poverty rate in the 51 states in the US (including DC) and high school graduation rate. The linear equation for predicting poverty is as follows: ŷ = 64.68 – 0.62x High school graduation rate for North Carolina is 81.4% and the poverty rate is 13.1%. What is the residual for this observation? Choose the closest answer. Do not change the percents into decimals to compute the residual. 18 16 14 12 10- 8 6. 80 85 90 % HS grad -24.8 24.8 -1.1 1.1 % in poverty
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…
The accompanying table shows results from regressions performed on data from a random sample of 21 cars. The response (y) variable is CITY (fuel consumption in mi/gal). The predictor (x) variables are WT (weight in pounds), DISP (engine displacement in liters), and HWY (highway fuel consumption in mi/gal). The equation CITY - 3.17 +0.823HWY was previously determined to be the best for predicting city fuel consumption. A car weighs 2700 lb, it has an engine displacement of 1.6 L, and its highway fuel consumption is 35 mi/gal. What is the best predicted value of the city fuel consumption? Is that predicted value likely to be a good estimate? Is that predicted value likely to be very accurate? Click the icon to view the table of regression equations. The best predicted value of the city fuel consumption is (Type an integer or a decimal. Do not round.). Regression Table I R² Adjusted R2 WT/DISP WT/HWY Predictor (x) Variables P-Value WT/DISP/HWY 0.000 0.942 0.000 0.748 0.000 0.942 0.000…
An ice cream truck owner collects data on the number of sales made each day and the average temperature that day. He computes a regression line for predicting the number of sales based on how far the daily temperature is from freezing (0 degrees Celsius) and finds sales = 3.22 - 1.8 (degrees over 0 Celsius). Identify the "y-intercept". A. -1.8 B. 1.8 C. 3.22 D. 0
In simple linear regression, the coefficient of determination measures: a.The amount of variability of the y variable that is explained by the x variable b.The amount of variability of the x variable that is explained by the y variable c.The amount of variability between the treatments d.The amount of variability within the treatments
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 = 21.592 + 0.324x, where x = price ($) and y = overall score. Brand Price ($) Score A 180 76 B 150 69 C 95 61 D 70 56 E 70 38 F 35 24 (a) Compute SST, SSR, and SSE. (Round your answers to three decimal places.) (b) Compute the coefficient of determination r2. (Round your answer to three decimal places.) (c) What is the value of the sample correlation coefficient? (Round your answer to three decimal places.)
There is a linear relationship between the number of chirps made by the stiped ground cricket and the air temperature. It was determined that the linear regression model is: y = 25.2 + 3.3x where x is the number of chirps per minute and y is the estimated temperature in degrees Fahrenheit. What is the temperature if a cricket chirps 18 times? Round to the nearest degree. Di not include units.

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