Answered: Compute the least-squares regression…

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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x	10	6	8	14	−7	−1	7	−9
y	3	1	30	31	0	3	−3	−15

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Find the slope (b1) for the regression equation for the following values. Round to 3 decimal places. Define Variables xi yi 33 180 25 170 50 200 65 186 57 160 27 165
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 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
A table of data points is given below. a. Find the regression equation for the data points. Use the formulas Sxx=∑ xi−x2 and Sxy=∑ xi−x yi−y to obtain Sxx and Sxy. b. Graph the regression equation and data points. x 1 2 3 y 6 5 10 a. The regression equation is y= + () x. (Simplify your answers. Type integers or decimals. Do not round.)
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The data provided give the number of standby hours based on total staff present, X₁, and remote hours, X₂. Perform a multiple regression analysis using the data provided and determine the VIF for each independent variable in the model. Is there reason to suspect the existence of collinearity? Click the icon to view the data. Determine the VIF for each independent variable in the model. | VIF ₂2 = VIF₁ = (Round to three decimal places as needed.) Is there reason to suspect the existence of collinearity? OA. No. The VIF for each independent variable is less than 5. B. Yes. The VIF for each independent variable is greater than 5. OC. No. The VIF for each independent variable is greater than 5. OD. Yes. The VIF for each independent variable is less than 5. wwwwwww Table of Data Standby Total Staff Hours Present 245 330 274 358 195 197 117 153 115 275 200 236 336 339 321 303 286 329 352 323 Remote Hours 417 655 524 385 349 350 388 153 278 479 Print Done
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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 pair of variables have a significant correlation.) Then use the regression equation to predict the value of y for each of the given x-values, if meaningful. The number of hours 6 students spent for a test and their scores on that test are shown below. Hours spent studying, x 1 2 2 3 4 6 Test score, y 39 44 52 47 64 70 (a)x=2hours (b)x=3.5hours (c)x=13hours (d)x=1.5hours Find the regression equation. y=______ x+ (_____) (Round the slope to three decimal places as needed. Round the y-intercept to two decimal places as needed.)

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Compute the least-squares regression equation for the given data set. Round the slope and y-intercept to at least four decimal places. x 10 6 8 14 −7 −1 7 −9 y 3 1 30 31 0 3 −3 −15 Regression line equation: y=