Given are five observations for two variables, and y.X2 7 10 12 1460 59 46 16 12YiThe estimated regression equation for these data is = 77.87-4.36x.a. Compute SSE, SST, and SSR..SSE(to 2 decimals)SST(to 2 decimals)SSR(to 2 decimals)b. Compute the coefficient of determination r2. Comment on the goodness of fit.(to 3 decimals)The least squares line provided an Select your answer fit;estimated regression equation (to 1 decimal).c. Compute the sample correlation coefficient. Enter negative value as negative number,(to 3 decimals)% of the variability in y has been explained by the

The estimated regression equation for the given data is .xiyi260759104612161412

Answered: Given are five observations for two…

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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Complete parts (a) through (c) using the following data. Row 1 1 Row 2 94 1 82 2 82 2 70 C 5 91 5 72 6 75 Input the values of the slope and intercept for the regression line when Row 1 represents the x-values. ŷ=x+ (Round to three decimal places as needed.) 6 81 6 65 8 69 2 (a) Find the equation of the regression line for the given data, letting Row 1 represent the x-values and Row 2 the y-values. Sketch a scatter plot of the data and draw the regression line.
a. Using the pairs of values for all 10 points, find the equation of the regression line. b. After removing the point with coordinates (2,8), use the pairs of values for the remaining 9 points and find the equation of the regression line.. c. Compare the results from parts (a) and (b). C a. What is the equation of the regression line for all 10 points? ŷ=+x (Round to three decimal places as needed.) b. What is the equation of the regression line for the set of 9 points? y = (Round to three decimal places as needed.) y= c. Choose the correct description of the results below. OA. The regression line changes, but the change is small. OB. The regression line is very similar in both cases. OC. There is no regression line for the second case because the data are in a pattern. On The removal of the point has a significant impact on the regression line 10 8- 0 ++++++ 0 2 4 6 8 10. OON
Listed below is the multiple regression equation for predicting Y by X₁ through Xs. Y is the number of sales per month. X₁ is the number of sales calls made X2 is the number of hours on the showroom floor X3 is the amount spent on radio ads X is the number of text messages sent Xs is the number of email messages sent Regression Statistics R Square 0.634 Standard Error 7.6796 Observations 45 Intercept X₁ X₂ X3 XA Xs Coefficients Standard Error 6.8163 0.1005 -0.3207 0.2084 0.1221 0.0943 77.1211 1.9439 -11.123 0.1144 11.34 1.23 What is the computed value of the F statistic you would use to test the significance of the entire model? Round your answer to two decimal places.
Use the given data to find the equation of the regression line. Round the final values to three significant digits, if necessary. 6 8 20 28 36 2 4 13 20 30 y OA. y = -2.79+0.897x OB. y = -3.79+0.897x OC. y=-3.79+0.801x OD. y = -2.79+0.950x TIE
Use the given data to find the equation of the regression line. Round the final values to three significant digits, if necessary. A horizontal table lists x-values in the first row and y-values in the second row. The x-values are as follows from left to right: 6, 8, 20, 28, and 36. The y-values are as follows from left to right: 2, 4, 13, 20, and 30. A. y with caret= −2.79 + 0.897x B. y with caret = −3.79 + 0.801x C. y with caret= −2.79 + 0.950x D. y with caret = −3.79 + 0.897x
5. For the following set of data: Y 1 10 5 4 4 13 a. Find the regression equation for predicting Y from X. b. Does the regression equation account for a significant portion of the variance in the Y scores? Use a = .05 to evaluate the F-ratio %3D X27 33
Given are five observations for two variables, z and y. z 3 9 10 18 20 | 53 55 50 14 16 The estimated regression equation for these data is y 70.38 – 2.73z. a. Compute SSE, SST, and SSR. SSE (to 2 decimals) 230 (to 2 decimals) (to 2 decimals) b. Compute the coefficient of determination. Comment on the goodness of fit. SST SSR (to 3 decimals) The least squares line provided an pood explained by the estimated regression equation (to 1 decimal). c. Compute the sample correlation coefficient. Enter negative value as negative number. % of the variability in y has been (to 3 decimals)

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