The table below shows the numbers of new-vehicle sales (in thousands) for Company 1 and Company 2 for 11 years.Construct and interpret a 99% prediction interval for new-vehicle sales for Company 2 when the number of new vehiclessold by Company 1 is 2766 thousand. The equation of the regression line is y = 1.208x+410.022.Company 1, xCompany 2, y4074 3966 3637 3416 3292 3083 2860 2474 19954932 4843 4799 4750 4666 4459 4050 3841 29651616 19482054 2234Construct and interpret a 99% prediction interval for new-vehicle sales for Company 2 when the number of new vehiclessold by Company 1 is 2766 thousand. Select the correct choice below and fill in the answer boxes to complete yourchoice.(Round to the nearest cent as needed.)A. We can be 99% confident that when the new-vehicle sales for Company 1 is 2766 thousand, the new-vehiclesales for Company 2 will be between and thousand.B. There is a 99% chance that the predicted new-vehicle sales for Company 2 is between and thousand,given that the new-vehicle sales for Company 1 is 2766 thousand.

Question: 1. Given information: - Regression equation: ŷ = 1.208x + 410.022 - x (Company 1…

Answered: The table below 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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Develop a scatterplot and explore the correlation between customer age and net sales by each type of customer (regular/promotion). Use the horizontal axis for the customer age to graph. Find the linear regression line that models the data by each type of customer. Round the rate of changes (slopes) to two decimal places and interpret them in terms of the relation between the change in age and the change in net sales. What can you conclude? Hint: Rate of Change = Vertical Change / Horizontal Change = Change in y / Change in x
when a regression is used as a method of predicting dependent variables from one or more independent variables. How are the independent variables different from each other yet related to the dependent variable?
A box office analyst seeks to predict opening weekend box office gross for movies. Toward this goal, the analyst plans to use online trailer views as a predictor. For each of the 66 movies, the number of online trailer views from the release of the trailer through the Saturday before a movie opens and the opening weekend box office gross (in millions of dollars) are collected and stored in the accompanying table. A linear regression was performed on these data, and the result is the linear regression equation Yi=−0.840+1.4108Xi. Determine the coefficient of determination,r2,and interpret its meaning. Determine the standard error of the estimate. How useful do you think this regression model is for predicting opening weekend box office gross? Can you think of other variables that might explain the variation in opening weekend box office gross?
please use this situation: A small theater company has a linear regression model to estimate y = the concession stand sales in dollars, based on knowing x = the number of people in attendance. The regression equation is: = 6.72x + 11.50 and the correlation coefficient was r = 0.781. The data set saw the number of people in attendance ranging from a minimum of 18 people to a maximum of 170 people. 1) How reliable would it be to make a prediction for the concession sales amount if there were 500 people in attendance? Explain.
A box office analyst seeks to predict opening weekend box office gross for movies. Toward this goal, the analyst plans to use online trailer views as a predictor. For each of the 66 movies, the number of online trailer views from the release of the trailer through the Saturday before a movie opens and the opening weekend box office gross (in millions of dollars) are collected and stored in the accompanying table. A linear regression was performed on these data, and the result is the linear regression equation Yi=−1.254+1.3968Xi. Complete parts (a) through (d). a. Determine the coefficient of determination,r2,and interpret its meaning. b. Determine the standard error of the estimate. c. How useful do you think this regression model is for predicting opening weekend box office gross? d. Can you think of other variables that might explain the variation in opening weekend box office gross?
The table below shows the average weekly wages (in dollars) for state government employees and federal government employees for 10 years. Construct and interpret a 99% prediction interval for the average weekly wages of federal government employees when the average weekly wages of state government employees is $925. The equation of the regression line is
The table below shows the average weekly wages (in dollars) for state government employees and federal government employees for 10 years. Construct and interpret a 90% prediction interval for the average weekly wages of federal government employees when the average weekly wages of state government employees is $825. The equation of the regression line is y = 1.597x- 169.203. Wages (state), x Wages (federal), y 742 775 783 802 842 890 912 939 949 954 1,002 1,039 1,097 1,145 1,199 1,242 1,271 1,299 1,335 1,398 Construct and interpret a 90% prediction interval for the average weekly wages of federal government employees when the average weekly wages of state government employees is $825. Select the correct choice below and fill in the answer boxes to complete your choice. (Round to the nearest cent as needed.) O A. There is a 90% chance that the predicted average weekly wages of federal government employees is between S and S given a state average weekly wage of $825. O B. We can be 90%…
The table below shows the average weekly wages (in dollars) for state government employees and federal government employees for 10 years. Construct and interpret a 95% prediction interval for the average weekly wages of federal government employees when the average weekly wages of state government employees is $895. The equation of the regression line is y = 1.454x- 36.984. Wages (state), x Wages (federal), y 712 778 789 801 843 878 927 937 939 958 1,014 1,054 1,116 1,146 1,191 1,248 1,270 1,302 1,335 1,401 Construct and interpret a 95% prediction interval for the average weekly wages of federal government employees when the average weekly wages of state government employees is $895. Select the correct choice below and fill in the answer boxes to complete your choice. (Round to the nearest cent as needed.) O A. We can be 95% confident that when the average weekly wages of state government employees is $895, the average weekly wages of federal government employees will be between $ and…
Construct and interpret a 95% prediction interval for the proceeds when the number of issues is 658.

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