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.6.7129.1014412y 736.7812.557.377.589.086.175.3186.545.58.....O A.O B.OC.D.Ay25-25-AY2525-20202020-151515-15510-10-10105-5-0-0 5 10 15 20 250 5 10 15 20 250 5 10 15 20 2505 10 15 20 25Find 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 an influential point that strongly affects the graph of the regression line.O B. There is no trend in the data.O C. The data has a pattern that is not a straight line.O D. There is no characteristic of the data that is ignored by the regression lineStatcrunchP Type here to searchhpf2米f5f6f8fgf10f1f12delete?insertprt scesc144&346.backspacehomeET.Ypg utabGKentercaps lockpause00%24%235.

Answered: Use the given data to find the equation…

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.
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:…
Consider the following data set, where y is the final grade in a math class and is the average number of hours the student spent working on math each week. hours/week X 6.5 10 11 12.5 13 14.5 15 17.5 19.5 20 Grade y 66.1 63 71.4 72.5 79.2 94.3 95 91.5 100 98 The regression equation is y = 3x + 41.3. a) Explain what the value of the slope means in this situation, where y is the final grade in a math class and is the average number of hours the student spent working on math each week. O For each additional hour per week that a student studies on average, their final grade will be about 3 points. O For each additional hour per week that a student studies on average, their final grade will be about 41.3 points higher. For each additional hour per week that a student studies on average, their final grade will be about 3 points higher. O For each additional hour per week that a student studies on average, their final grade will be about 41.3 points. b) Explain what the value of the…
1. 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 y 7.20 12 6 7.04 6.16 13 4 5.94 3.04 3 0.94 y = __ __ x (Round to two decimal places as needed.) 10 8.16 9 8.20 11 7.78 5 8 4.78 7.88
9. Find the equation of the regression line for the given data. Then construct a scatter plot of the data and draw the regression line. (Each pair of variables has a significant correlation.) Then use the regression equation to predict the value of y for each of the given x-values, if meaningful. The caloric content and the sodium content (in milligrams) for 6 beef hot dogs are shown in the table below. Calories, x Sodium, y 160 130 330 120 70 190 (a) x = 170 calories (c) x = 150 calories 180 (b) x = 80 calories 420 470 360 250 530 (d) x = 210 calories Find the regression equation. x+( (Round to three decimal places as needed.) y = Choose the correct graph below. OA. О В. OC. OD. 560- 560 560 560- 200 G 0IN T> 200 200 Calories Calories Calories Calories (a) Predict the value of y for x = 170. Choose the correct answer below. O A. 411.632 O B. 543.752 O C. 455.672 O D. not meaningful (b) Predict the value of y for x = 80. Choose the correct answer below. O A. 411.632 О В. 257.492 O C.…
The personnel director of a large hospital is interested in determining the relationship (if any) between an employee's age and the number of sick days the employee takes per year. The director randomly selects ten employees and records their age and the number of sick days which they took in the previous year. Employee 1 | 2 4 6 7 8 10 5 30 50 40 30 28 Age 55 60 25 30 45 Sick Days 7 4 3 9 10 8 5 2 Copy Data The estimated regression line and the standard error are given. Sick Days 14.310162 – 0.2369( Age Se = = 1.682207 Find the 95 % confidence interval for the average number of sick days an employee will take per year, given the employee is 26. Round your answer to two decimal places. 2.
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 6 10 8 9 11 12 13 y 10.46 16.87 14.27 15.72 17.71 18.26 18.49 y=+x (Round to two decimal places as needed.) 5 8.09 4 5.42 14 7 18.42 12.51
6. Which of the following are true? Select all that apply. a. The coefficient of determination is the proportion of variation in the response variable that is explained by the regression line. b. We often use the symbol r to represent the coefficient of determination. c. In simple linear regression, the coefficient of determination equals the square of the linear correlation coefficient r. d. The closer the regression line comes to the data points, r should go to eleven.
The personnel director of a large hospital is interested in determining the relationship (if any) between an employee's age and the number of sick days the employee takes per year. The director randomly selects ten employees and records their age and the number of sick days which they took in the previous year. Employee 1 2 3 4 5 6 7 8 Age 30 50 40 55 30 28 60 25 Sick Days 7 4 3 2 9 10 0 8 Copy Data The estimated regression line and the standard error are given. Sick Days = 14.310162 - 0.2369(Age 9 10 30 45 5 2 Se = 1.682207 Find the 95% confidence interval for the average number of sick days an employee will take per year, given the employee is 26. Round your answer to two decimal places.
Run a regression analysis on the following bivariate set of data with y as the response variable. y 56.3 -257.6 14.5 670.8 49.4 431 60.7 200.3 60.1 70.3 52.6 -162.4 46.2 -406.9 45.1 -3.6 39.6 292.4 51.2 274.8 53.1 -77.4 50 496.6 46.9 251.5 48.5 -188.7 79.8 233 33.5 -415.6 49.2 431.3 download link provided here: Download CSV Predict what value (on average) for the response variable will be obtained from a value of 32.1 as the explanatory variable. Use a significance level of a = 0.05 to assess the strength of the linear correlation. What is the predicted response value? y = 169.94127 (Report answer accurate to one decimal place.)

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