The table shows the numbers of new-vehicle sales (in thousands) in the United States for Company A andCompany B for 10 years. The equation of the regression line is y = 0.977x + 1,252.74. Complete parts (a)and (b) below.New-vehiclesales(Company A), xNew-vehiclesales(Company B), y4,167 3,904 3,581 3,428 3,250 3,124 2,868 2,494 1,925 2,0754,909 4,869 4,828 4,718 4,640 4,452 4,659 3,829 2,943 2,798(a) Find the coefficient of determination and interpret the result.2=0(Round to three decimal places as needed.)

The question is about regression.Given :Regression equation :To find :Value of coefficient of…

Answered: The table shows the numbers of…

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 relationship between the cost of a concert ticket and a ranking of the performer's popularity was summarized by a regression equation with slope of 135 and y-intercept of -373. What is the equation of the regression line? cost =+ (O popularity Enter your answer in each of the answer boxes. tv 12 MacBook Air DD 888 esc F7 F8 F9 F5 F6 F1 F2 F3 F4
Refer to the data set: (1, 2.5), (2.5, 15), (0.5, 2), (-2, 0.5), (0, 1), (1.5, 5)Part a: Make a scatterplot and determine which type of model best fits the data.Part b: Find the regression equation, round decimals to one place.Part c: Use the equation from Part b to determine y when x = 6.
What is the linear regression of the data? y = x- 1,3,5,7,9, y- 3,7,13,17,23 (Use integers or decimals for any numbers in the expression. Round to the nearest tenth as needed)
Fourteen hikers were surveyed at Algonquin Park, and asked for how many days have you been hikingand far did your travel in that time? The equation for the linear regression line is y+3x + 10.3 where x is the number of days and y is the distance travelled. What does the slope imply? and does this make sense. Number of days hiked 1 1 2 3 3 5 5 6 7 7 9 10 11 12 Distance Traveled (km) 12 17 18 19 21 23 25 23 30 31 37 39 41 52
The table shows the average weekly wages (in dollars) for state government employees and federal government employees for 8 years. The equation of the regression line is y = 1.530x-123.860. Complete parts (a) and (b) below. Average Weekly Wages (state), x Average Weekly Wages (federal), y 762 992 (a) Find the coefficient of determination and interpret the result. 2-0 (Round to three decimal places as needed.) How can the coefficient of determination be interpreted? 773 1044 Se (Round to two decimal places as needed.) How can the standard error of estimate be interpreted? The coefficient of determination is the fraction of the variation in average weekly wages for average weekly wages for and is represented by due to other factors or to sampling error. (b) Find the standard error of estimates and interpret the result. 796 1117 The standard error of estimate of the average weekly wage for is about s dollars. 817 1155 844 1196 for 878 1252 The remaining fraction of the variation, 931 1281…
The annual profits for a company are given in the following table, where x represents the number of years since 2004, and y represents the profit in thousands of dollars. Write the linear regression equation that represents this set of data, rounding all coefficients to the nearest tenth. Using this equation, find the projected profit (in thousands of dollars) for 2012, rounded to the nearest thousand dollars. Years since 2004 (x) Profits (y)(in thousands of dollars) 0 110 1 137 2 135 3 141 4 160 5 172
a) Determine a linear regression equation for the data. Round the slope and y-intercept to the nearest whole number. b) Find the correlation coefficient, r-value, of the line. Round your answer to the nearest thousandth. c) Predict the distance the driver would have traveled after 11 hours. Round your answer to the nearest whole number.
The data below is the amount of tar and nicotine in a sample of different brands of 100 mm, non-menthol, filtered cigarettes. a) Using the calculator, find a linear regression model that gives the amount of nicotine, N, as a function of the amount of tar, t. Write the function below. N(t)= b) use this model of nicotine to estimate the amount of nicotine in a cigarette if the amount of tar is listed as 21 mg. c) What is the correlation coefficient, r, for this model? r= Tar 5 16 17 13 13 14 9 15 2 15 13 14 15 16 7 17 Nicotine 0.4 1 1.2 0.8 0.8 1 0.8 1 0.2 1.1 0.8 1 0.9 1.1 0.6 1.3
The following data show the brand, price ($), and the overall score for six stereo headphones that were tested by a certain magazine. The overall score is based on sound quality and effectiveness of ambient noise reduction. Scores range from 0 (lowest) to 100 (highest). The estimated regression equation for these data is ŷ = 24.064 + 0.309x, where x = price ($) and y = overall score. Brand Price ($) Score A 180 74 B 150 73 C 95 61 D 70 54 E 70 40 F 35 28 (a) Compute SST, SSR, and SSE. (Round your answers to three decimal places.) SST = SSR = SSE = (b) Compute the coefficient of determination r2. (Round your answer to three decimal places.) r2 = Comment on the goodness of fit. (For purposes of this exercise, consider a proportion large if it is at least 0.55.) The least squares line provided a good fit as a small proportion of the variability in y has been explained by the least squares line.The least squares line provided a good fit as a large proportion of…
Lillian conducted a small survey of her friends and family. She asked them how many hours per week they spend reading digital documents (newspapers, blogs, books, etc.), and their age. She created the scatter plot below with the results she obtained. Draw the regression line that best represents this scatter plot and determine its equation.
The following data show the brand, price ($), 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 = 21.656 + 0.333x, where x = price ($) and y = overall score. Brand Price ($) Score A 180 76 B 150 73 95 61 70 54 E 70 42 35 24 (a) Compute SST, SSR, and SSE. (Round your answers to three decimal places.) SST = SSR = SSE = (b) Compute the coefficient of determination r. (Round your answer to three decimal places.) 12 = Comment on the goodness of fit. (For purposes of this exercise, consider a proportion large if it is at least 0.55.) O The least squares line did not provide a good fit as a small proportion of the variability in y has been explained by the least squares line. O The least squares line provided a good fit as a small proportion of the variability in y…
A temperature dataset gives y mean April temperature (Fahrenheit) and x = geographic latitude for 20 U.S. cities. The simple linear regression equation for the sample is ŷ = 119 - 1.64x. (a) The value of latitude for a certain city is 41. What is the predicted April temperature for this city? (Round your answer to the nearest tenth.) degrees Fahrenheit (b) The mean April temperature for this city is 48. What is the residual for the city? (Round your answer to the nearest tenth.) degrees Fahrenheit You may need to use the appropriate table in the Appendix of Tables to answer this question.

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