Average Age and Length of Service The data show the average ages and lengths of service in months.Age24.925.5 26.1 26.8 26.8Time66.769.7 73.3 89 82.5Send data to ExcelThe correlation coefficient for the data is r=0.932 and α=0.05. Should regression analysis be done?The regression analysis should not be done.O The regression analysis should be done.Find the equation of the regression line. Round the coefficients to at least three decimal places.y' = a + bxa =b =If a service person is 26.6 years old, predict the time that the person will serve. Round the answer to at least onedecimal place.The service person will serve months.X

Given Correct option is 2nd The regression analysis should be done. >> The critical value for…

Answered: 25.5 26.1 26.8 26.8 me 69.7 73.3 89…

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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Use the given data to find the equation of the regression line. Examine the scatterplot and identify a characteristic of the data that is ignored by the regression line. 12 10 14 13 6 y 7.26 6.82 12.79 7.28 7.92 9.07 6.29 5.46 8.45 6.44 6.02 Create a scatterplot of the data. Choose the correct graph below. O B. Oc. OD. 25- 25 25- 25- 20- 20- 20 205 15 15 15 15 10- 105 10- 10 53 07 0 5 10 15 20 25 0 5 10 15 20 25 0 5 10 15 20 25 o 5 10 15 20 25 8.
Find the equation of the regression line for the given data. Then construct a scatter plot of the data and draw the regression line. The table shows the shoe size and heights (in.) for 6 men. Shoe size, x Height, y 7.5 66.5 Find the regression equation. ŷ=x+ y (Round to three decimal places as needed.) 9.5 69.5 10.5 70.5 11.0 72.5 13.0 72.5 13.5 73.5
Use the given data to find the equation of the regression line. Examine the scatterplot and identify a characteristic of the data that is ignored by the regression line. 9 9 11 10 11 14 4 13 7 6 y 7.59 6.87 13.06 7.32 8.58 6.09 5.62 8.35 6.73 7.77 5.9 Create a scatterplot of the data. Choose the correct graph below. O A. OB. OC. Oc. OD. Ay 25- Ay 25- Ay 25- 25- 20 20- 20- 20- 155 155 155 155 105 105 105 105 5- 55 55 55 0- Ó 5 10 15 20 25 0- 0- 05 10 15 20 25 Ó 5 10 15 20 25 0 5 10 15 20 25 Find the equation of the regression line. (Round the constant two decimal places as needed. Round the coefficient to three decimal places as needed.) Identify a characteristic of the data that is ignored by the regression line. O A. The data has a pattern that is not a straight line. O B. There is no characteristic of the data that is ignored by the regression line. OC. There is an influential point that strongly affects the graph of the regression line. O D. There is no trend in the data.
A sales manager for an advertising agency believes there is a relationship between the number of contacts that a salesperson makes and the amount of sales dollars earned. A regression analysis shows the following results. Coefficients Standard Error t-Stat p-value Intercept −12.201 6.560 −1.860 0.100 Number of contacts 2.195 0.176 12.505 0.000 What is the regression equation? Multiple Choice Ŷ = 2.195 − 12.201X Ŷ = −12.201 + 2.195X Ŷ = 12.201 + 2.195X Ŷ = 2.195 + 12.201X
Use StatKey or other technology to find the regression line to predict Y from X using the following data. Click here to access StatKey. Round your answers to three decimal places. The regression equation is Y = X 6 Y 3.5 10 8 + 4 2 14 12 12 8.5 X.
The data show the chest size and weight of several bears. Find the regression equation, letting chest size be the independent (x) variable. Then find the best predicted weight of a bear with a chest size of 40 inches. Is the result close to the actual weight of 352 pounds? Use a significance level of 0.05. Chest size (inches) *Weight (pounds) 44 54 328 528 41 55 39 51 418 580 296 503 Click the icon to view the critical values of the Pearson correlation coefficient r. - What is the regression equation? x (Round to one decimal place as needed.)
Use the value of the linear correlation coefficient to calculate the coefficient of determination. What does this tell you about the explained variation of the data about the regression line? About the unexplained variation? r= - 0.884 Calculate the coefficient of determination. (Round to three decimal places as needed.)
Use the given data to find the equation of the regression line. Examine the scatterplot and identify a characteristic of the data that is ignored by the regression line. x 11 7 11 10 12 14 6 4 11 8 5 y 7.6 6.6 13.07 7 7.67 9.18 5.81 5.46 8.04 6.52 5.99 Create a scatterplot of the data. Choose the correct graph below. A. 05101520250510152025xy A scatterplot has a horizontal x-scale from 0 to 25 in intervals of 1 and a vertical y-scale from 0 to 25 in intervals of 1. Eleven points are plotted with approximate coordinates as follows: (4, 8); (5, 6); (6, 6.5); (7, 6.5); (8, 9); (10, 7.5); (11, 5.5); (11, 7); (11, 13); (12, 6); (14, 7.5). B. 05101520250510152025xy A scatterplot has a horizontal x-scale from 0 to 25 in intervals of 1 and a vertical y-scale from 0 to 25 in intervals of 1. Eleven points are plotted with approximate coordinates as follows:…
answer this. not graded
r = -0.579 Calculate the coefficient of determination. (Round to three decimal places as needed.) What does this tell you about the explained variation of the data about the regression line? % of the variation can be explained by the regression line. (Round to one decimal place as needed.) About the unexplained variation? % of the variation is unexplained and is due to other factors or to sampling error. (Round to one decimal place as needed.)
Use the given data to find the equation of the regression line. Examine the scatterplot and identify a characteristic of the data that is ignored by the regression line. 11 8 11 13 6 13 6 y 7.24 6.87 12.78 6.87 7.75 8.85 6.28 5.61 8.28 6.72 5.52 Create a scatterplot of the data. Choose the correct graph below. VA. OB. OC. OD. 25- Ay 25- 25- 25- 20- 20 20- 20 15 155 155 155 10- 10- 10 10- 5- 5- 5 55 0- 05 10 15 20 25 0- O 5 10 15 20 25 04 05 10 15 20 25 0- 05 10 15 20 25 Find the equation of the regression line. (Round the constant two decimal places as needed. Round the coefficient to three decimal places as needed.)
Use the value of the linear correlation coefficient to calculate the coefficient of determination. What does this tell you about the explained variation of the data about the regression line? About the unexplained variation?

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