The table shows the numbers of new-vehicle sales (in thousands) in the United States for Company A and Company Bfor 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), xNew-vehicle sales(Company B), y4,149 3,923 3,566 3,400 3,266 3,076 2,868 2,485 1,952 2,0664,912 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 be2explained by the variation in new-vehicle sales for Company A and is represented byThe remainingfraction 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.SeO(Round to three decimal places as needed.)H CH11✓ ✓UIMoreXIr

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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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Please all the 3 of these sub-questions. Make sure answer is rounded up to 4 decimals
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. D 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. 12²=0 (Round to three decimal places as needed.) 1
37-38. Given the following data pairs (x, y): (1, 1.24), (2, 5.23). (3, 7.24). (4, 7.60), (5, 9.97), (6, 14.31), (7, 13.99).(8, 14.88), (9, 18.04), (10, 20.70). Find the regression equation O A. y = 0.490 x - 0.053 O B. y = 2.04 x O C. y = 1.98 x + 0.436 O D. y = 0.49 x
The table shows the amounts of crude oil (in thousands of barrels per day) produced by a certain country and the amounts of crude oil (in thousands of barrels per day) imported by the same country for seven years. The equation of the regression line is y =-1.364x+17,178.20. Complete parts (a) and (b) below. Produced, x Imported, y 5,744 5,554 5,439 5,188 5,136 5,067 D 9,132 9,677 10,017 10,193 10,149 10,075 5,756 9,328 (a) Find the coefficient of determination and interpret the result. (Round to three decimal places as needed.)
The number of initial public offerings of stock issued in a 10-year period and the total proceeds these offerings (in millions) are shown in the table. The equation of the regression line is y = 43.977x+ 19,528.57. Complete parts a and b. 379 55 18,716 29,004 42,559 30,325 67,231 65,155 21,100 12,473 31,455 27,712 Issues, x 424 457 695 500 499 74 180 158 Proceeds. (a) Find the coefficient of determination and interpret the result. (Round three decimal places as needed.)
Choose the correct answer of each number. 1. An analyst hired by the multinational company to study the sales data of its more than 75 stores worldwide. Used regression analysis to predict $ sales (y) by using $ advertising (x1) and $ salary of sales representatives (x2) across all the branches. You obtained the following regression function: y = 7800 + 8.5x1-1.6x2. If the advertising budgets of one of the branches of the corporation is now $45,000 (which is 10% more than before) and the salary of sales representatives is now $8,500 (which is 20% less than before), then the predicted sales before in that branch is a. $417,750 b. $341,250 c. $376,700 d. $335,6502. An analyst hired by the multinational company to study the sales data of its more than 75 stores worldwide. Used regression analysis to predict $ sales (y) by using $ advertising (x1) and $ salary of sales representatives (x2) across all the branches. You obtained the following regression function: y = 7800 + 8.5x1-1.6x2. If…
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 = 516.388x - 1699.161. Complete parts a and b. Total Square Footage, X Sales, y 4.9 5.1 5.2 5.4 5.6 5.7 ********** (a) Find the coefficient of determination and interpret the result. 5.9 5.8 (Round to three decimal places as needed.) How can the coefficient of determination be interpreted? 5.9 883.3 937.6 986.3 1059.5 1107.2 1200.9 1281.1 1340.8 1438.2 1536. 6.2 OA. 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 other factors or to sampling error. OB. 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 is…
Explain how to find se
8
The table shows the amounts of crude oil (in thousands of barrels per day) produced by a certain country and the amounts of crude oil (in thousands of barrels per day) imported by the same country for seven years. The equation of the regression line is y = - 1.269x + 16,635.60. Complete parts (a) and (b) below. Produced, x Imported, y 5,718 5,612 5,409 5,228 5,128 5,006 O 9,106 9,631 10,000 10,140 10,133 10,059 5,759 9,318 (a) Find the coefficient of determination and interpret the result. (Round to three decimal places as needed.)
H. Find the slope and y-intercept of each regression line. Then, determine if the correlation between the variables is positive or negative. (12 points) Regression Line Equation 1. Y = 1.751X – 21.722 Slope y-intercept Kind of Correlation 2. Y = -221.943X+65.434 3. Y = -82.455X –314.986 4. Y = 0.997X + 0.168
The sales of a company (in million dollars) for each year shown in the table below (25)X(year) 2005 2006 2007 2008 2009Y (sales) 12 19 39 37 45a. Find the regression line of the data. Draw the inference about the dataset.b. Use the regression line as a model to estimate the sales of the company in 2012.

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