27. Consider the data in the following table regardingrevenue generated in a company during a recent 3-yearperiod. [6.4]REVENUE, y(in millions)YEAR, x12738a) Find the regression line, y = mx + b.b) Use the regression line to predict the revenue in thefourth year.

Given, Year, X Revenue, Y 1 5 2 7 3 8

Answered: 27. Consider the data in 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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Suppose data is found showing the demand for a product and its price (in dollars) in different market areas where the demand values ranged from 18 to 90. Furthermore, the goal is to use the data to construct a model that will be used to predict the price for the product in terms of its demand. Further, suppose the regression line is found to be y = 23.51535 – 0.09035z The- price for the product when the demand is 160 is: O The average price is 23.51535 - 0.09035(160) = $9.06 anytime the demand is 160 O The average price is 23.51535 - 0.09035(160) = $9.06 for this specific time that the demand is 160 O The price is 23.51535 - 0. 09035(160) = $9 06 anytime the demand is 60 The price is 23.51535 - 0.09035(160) = $9.06 for this specific time that the demand is 60 O The answer cannot be found due to extrapolation
A company has a set of data with employee age (X) and the corresponding number of annual on-the-job-accidents (Y). Analysis on the set finds that the regression equation is Y=60-0.5*X. What can be said of the correspondence (relation) between age and accidents? Are younger workers safer or more prone to accident? What is the likely number of accidents for someone aged 25?
8. A study was conducted to determine the relationship between employee job satisfaction and job performance. The result of the regression analysis produced the model below: Job Performance (y) = 0.18+0.95 Job Satisf action (x) Which of the following statements is true about the equation? a. Job performance is independent of job satisfaction; such that, for every 1 unit change in Job Satisfaction, there is a 0.95 unit change in job performance. b. Job satisfaction is independent of job performance; such that, for every 1 unit change in Job performance, there is a 0.95 unit change in job satisfaction. C. Job performance is dependent on job satisfaction; such that, for every 1 unit change in job satisfaction, there is a 0.95 unit change in job performance. d. Job satisfaction is dependent on job performance; such that, for every 1 unit change in job satisfaction, there is a 0.95 unit change in job performance. e. Job satisfaction is not related to job performance.
The following is data on sales volume (million units) of cars linked to the promotion cost variable (X1 in million rupiah/year) and the variable cost of adding accessories (X2 in hundreds of thousands of rupiah/unit). Determine the regression equation.!
The United States gross national product, in trillions of dollars, is given in the table below. Date Gross national product 15.0 2010 2011 15.5 16.2 |2012 | 2013 16.7 (a) Find the equation of the regression line. (Let t be the number of years since 2010. Round regression line parameters to two decimal places.) Gt) = Explain the me aning of its slope. The slope of the line tells us that each year the gross national product increases by trillion dollars. (b) Plot the data points and the regression line. G 17 17 16 16 15 15 14 14 13 13 12 12 1 2 3 1 2 3 G G 17 17 16 16 15 15 14 14 13- 13 12 12 1 2 3 1 2 3 (c) When would you predict that a gross national product of 17.3 trillion dollars would be reached? (Round your answer to two decimal places.) The actual gross national product in 2014 was 17.3 trillion dollars. What does that say about your prediction? • This prediction is accurate. O This prediction is not accurate.
The table below shows the amounts of crude oil (in thousands of barrels per day) produced by a country and the amounts of crude oil (in thousands of barrels per day) mported by a country, for the last seven years. Construct and interpret a 95% prediction interval for the amount of crude oil imported by the this country when the amount of crude oil produced by the country is 5,508 thousand barrels per day. The equation of the regression line is y = - 1.120x + 15,839.271. Oil produced, x 5,684 5,654 5,452 5,157 5,061 5,030 5,826 9,680 10,041 10,154 10,121 10,060 Oil imported, y 9,304 9,105 Construct and interpret a 95% prediction interval for the amount of crude oil imported when the amount of crude oil produced by the country is 5,508 thousand barrels per day. Select the correct choice below and fill in the answer boxes to complete your choice. (Round to the nearest cent as needed.) and O A. We can be 95% confident that when the amount of oil produced is 5,508 thousand barrels, the…
The number of initial public offerings of stock issued in a 10-year period and the total proceeds of these offerings (in millions) are shown in the table. The equation of the regression line is y = 46.360x + 18,657.31. Complete parts a and b 412 455 Issues, x. Proceeds, 17,955 27,527 43,371 30,734 66,292 65,063 22,264 11,783 31,116 27,537 685 476 483 384 54 75 194 170 (a) Find the coefficient of determination and interpret the result. (Round to three decimal places as needed.) How can the coefficient of determination be interpreted? The coefficient of determination is the fraction of the variation in proceeds that is unexplained and is due to other factors or sampling error. The remaining fraction of the variation is explained by the variation in issues. The coefficient of determination is the fraction of the variation proceeds that can be explained by the variation in issues. The remaining fraction of the variation is unexplained and is due to other factors or to sampling error. (b)…
The table below shows the amounts of crude oil (in thousands of barrels per day) produced by a country and the amounts of crude oil (in thousands of barrels per day) imported by a country, for the last 7 years. Construct and interpret a 98% prediction interval for the amount of oil imported by the country and the amount of oil produced by the country is 5,483 thousand barrels per day. The equation of the regression line is y = -1.194x + 16,234.906
The table shows the numbers of new-vehicle sales (in thousands) in the United States for Company A and Company B for 10 years. The equation of the regression line is y = 0.991x + 1,222.81. Complete parts (a) and (b) below. New-vehicle sales (Company A), x New-vehicle sales (Company B), y 4,149 3,923 3,566 3,400 3,266 3,076 2,868 2,485 1,952 2,066 4,912 4,871 4,827 4,721 4,672 4,474 4,684 3,822 2,956 2,754 (a) Find the coefficient of determination and interpret the result. r² = r2 = 0.821 (Round to three decimal places as needed.) How can the coefficient of determination be interpreted? The coefficient of determination is the fraction of the variation in new-vehicle sales for Company B that can be 2 explained by the variation in new-vehicle sales for Company A and is represented by The remaining fraction of the variation, 1-2, is unexplained and is due to other factors or to sampling error. s (b) Find the standard error of estimates and interpret the result. Se O (Round to three decimal…
(d)Assess the regression model's fit
The table shows the total square footage (in billions) of retailing space at shopping centers and their sales (in billions of dollars) for 10 years. The equation of the regression line is y = 674.071x- 2582.997. Complete parts a and b. Total Square Footage, x Sales, y 5.1 5.2 5.3 5.4 5.5 5.6 5.7 5.9 5.9 6.1 852.7 927.6 978.6 1057.5 1104.2 1221.6 1277.9 1325.5 1439.3 1530.9 (a) Find the coefficient of determination and interpret the result. (Round to three decimal places as needed.) How can the coefficient of determination be interpreted? O A. The coefficient of determination is the fraction of the variation in sales that is unexplained and is due to other factors or sampling error. The remaining fraction of the variation explained by the variation in total square footage. O B. The coefficient of determination is the fraction of the variation in sales that can be explained by the variation in total square footage. The remaining fraction of the variation is unexplained and is due to…
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 = 1.405x – 12.307. Complete parts (a) and (b) below. Average Weekly Wages (state), x Average Weekly Wages (federal), y 751 760 791 817 835 881 924 951 1002 1047 1115 1149 1195 1250 1269 1300 (a) Find the coefficient of determination and interpret the result. 12 =O

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27. Consider the data in the following table regarding revenue generated in a company during a recent 3-year period. [6.4] REVENUE, y (in millions) YEAR, x 1 2 7 3 8 a) Find the regression line, y = mx + b. b) Use the regression line to predict the revenue in the fourth year.