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 12 3 4 9 10 8 7 11 6 13 5 y 13.79 4.32 6.59 13.37 13.81 12.62 11.57 13.96 10.21 13.32 8.56

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 12 3 4 9 10 8 7 11 6 13 5 y 13.79 4.32 6.59 13.37 13.81 12.62 11.57 13.96 10.21 13.32 8.56

MATLAB: An Introduction with Applications

6th Edition

ISBN:9781119256830

Author:Amos Gilat

Publisher:Amos Gilat

Chapter1: Starting With Matlab

Section: Chapter Questions

Problem 1P

See similar textbooks

x	12	3	4	9	10	8	7	11	6	13	5
y	13.79	4.32	6.59	13.37	13.81	12.62	11.57	13.96	10.21	13.32	8.56

Similar questions

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 7 13 8 12 14 4 12 8 5 У 7.53 6.85 12.72 7.2 7.45 8.44 6.25 5.14 7.88 6.73 5.85 Create a scatterplot of the data. Choose the correct graph below. O A. B. C. D. Ay 25- Ay 25- Ay 25- Ay 25- 20 20- 20 20- 15 155 15 15 10 10- 105 105 5- 55 5- 55 0- 0- 0- 0- 10 15 20 25 10 15 20 25 5 10 15 20 25 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.)
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 58 inches. Is the result close to the actual weight of 572 pounds? Use a significance level of 0.05. Chest size (inches) 46 57 53 41 40 40 Weight (pounds) 384 580 542 358 306 320 LOADING... Click the icon to view the critical values of the Pearson correlation coefficient r. What is the regression equation? y=nothing+nothingx (Round to one decimal place as needed.)
A. run a simple regression- dependent variable is Weeks, independent variable is Age. B. run a multiple regression with dependent variable weeks and independent variable-age, married, head, manager and sales. C. Create the regular and standardized residual plots for both. Please show the tables when entering values of the regression for both the outputs and the scatter plots.
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 7 14 10 11 15 12 6. 13 9. у 5.27 6.91 7.95 8.18 1.83 5.83 8.09 3.71 7.67 7.38 6.49 x (Round to two decimal places as needed.) %3D + Create a scatterplot of the data. Choose the correct graph below. A. В. OC. O D. .y 25- Ay 25- y 25- 25- 20- 20- 20- 20- 15- 15 15- 15- 103 105 103 105 5- 5극 53 5극 X X 0- 0- 0- 0 5 10 15 20 25 5 10 15 20 25 05 10 15 20 25 5 10 15 20 25 Identify a characteristic of the data that is ignored by the regression line. A. There is no trend in the data. B. There is an influential point that strongly affects the graph of the regression line. C. The data has a pattern that is not a straight line. D. There is no characteristic of the data that is ignored by the regression line. bo00 0
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. 8 11 9. 11 14 4 12 y 7.47 6.66 13.28 7.1 7.59 8.43 6.09 5.39 7.9 6.48 5.65 O A. OB. Oc. OD. Ay 25- Ay 25- Ay 25- AV 25- 20 20 20 20 15 15- 15- 15 10 10- 10- 10- 55 51 5- 0- Ó 5 10 15 20 25 0- 05 10 15 20 25 0- 5 10 15 20 25 O 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. There is an influential point that strongly affects the graph of the regression line. O B. There is no characteristic of the data that is ignored by the regression line. O C. The data has a pattern that is not a straight line. D. There is no trend in the data.
Based on the data shown below, use software such as Excel to calculate the slope and y-intercept and determine the regression line. y 22.4 3 19.35 4 22.3 21.15 21.9 7 20.35 8. 21.6 19.95 10 20 Round each value to two decimal places. Submit and End Priv Terr OCT 21 MacBook Pro 000 esc F5 F6 F7 F3 F4 F1 2$ & 4 5 6 Q W T Y tab RI # 3
Use the given data to find the equation of the regression line. Examine the scaterplot and identify a characteristic of the data that is ignored by the regression line. x 11 y 734 11 6.48 12.77 8 12 7.66 13 9.05 4 13 7.98 7. 6.59 7.38 5 85 5.48 5.99 Create a scatterplot of the data. Choose the correct graph below OA. OB. C. OD. 25 Ar 25 AY 25 25 20 201 20 20 15- 15 10 154 15 10 10 10 0 10 15 20 25 0510 15 20 25 68 10 15 le 05 10 15 2o 25 Find the equation of the regression line. (Round the y-intercept two decimal places as needed. Round the slope to three decimal places as needed) Identily a characteristic of the data that is ignored by the regression line OA There is no characteristic of the data that is ignored by the regression ine OB There is an influential point that strongly affects the graph of the regression line OC The data has a pattem that is not a straight Iine OD. There is no trend in the data.
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 7.44 11 9. 13 12.76 13 8.53 4 5.48 12 7.96 6. y 7.27 6.65 6.89 6.3 6.23 5.91 Create a scatterplot of the data. Choose the correct graph below. O A. O B. Oc. O D. 25 25- 25 Ay 25 20- 20- 20 20- 155 155 15 15 105 105 10- 105 55 55 53 05 10 15 20 25 05 10 15 20 25 05 10 15 20 25 05 10 15 20 25 Find the equation of the regression line. (Round the y-intercept two decimal places as needed. Round the slope to three decimal places as needed) Identify a characteristic of the data that is ignored by the regression line, O A. There is no characteristic of the data that is ignored by the regression line. O B. There is an influential point that strongly affects the graph of the regression line. C. There is no trend in the data. O D. The data has a pattern that is not a straight line. 5,
Create a scatterplot of the data. Choose the correct graph Identify a characteristic of the data that is ignored by the regression line.
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 12 10 6 13 14 7 5 4 8 9 y 14.34 14.30 14.01 8.90 13.86 13.05 10.74 6.66 4.05 12.21 13.31
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.)
y 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 7 4 13 13 10 12 14 13.32 6.78 7.89 8.93 5.83 5.44 y 7.59 6.64 8.05 7 5 D 6.3 5.94 (...) OA. B. O D. Q 25- Q 25- 20 20 15 Q Q 155 10 10- O C. 25+ 20 153 5- DOOR P 28 10 5- 0 5 0 5 10 15 20 25 0 5 10 15 20 25 0- 0 5 10 15 20 25 Find the equation of the regression line. y=0+0x (Round the y-intercept two decimal places as needed. Round the slope to three decimal places as needed.) Identify a characteristic of the data that is ignored by the regression line. OA. There is no characteristic of the data that is ignored by the regression line. B. The data has a pattern that is not a straight line. OC. There is an influential point that strongly affects the graph of the regression line. Av Ay 25 20 15: 10 Q Q Aу Ay / 53 0 0 5 10 15 20 25