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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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
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The table shows the amounts of crude oil (in thousands of barrels per day) produced by a certain country and the amounts of crude oil (in thousands of barrels per day) imported by the same country for seven years. The equation of the regression line is y =-1.364x+17,178.20. Complete parts (a) and (b) below. Produced, x Imported, y 5,744 5,554 5,439 5,188 5,136 5,067 D 9,132 9,677 10,017 10,193 10,149 10,075 5,756 9,328 (a) Find the coefficient of determination and interpret the result. (Round to three decimal places as needed.)
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Fill in the blanks. a. Multicollinearity is considered to be severe if the VIF for one or more predictor variables is ______. or greater. b. If the coefficient of multiple determination for the regression of the predictor variable x11 on all the other predictor variables in a regression equation is 0.6, then the VIF for x1 is ______. c. The effect of multicollinearity in a polynomial regression analysis can be reduced by ______. the predictor variable.
The table shows the amounts of crude oil (in thousands of barrels per day) produced by a certain country and the amounts of crude oil (in thousands of barrels per day) imported by the same country for seven years. The equation of the regression line is y = - 1.269x + 16,635.60. Complete parts (a) and (b) below. Produced, x Imported, y 5,718 5,612 5,409 5,228 5,128 5,006 O 9,106 9,631 10,000 10,140 10,133 10,059 5,759 9,318 (a) Find the coefficient of determination and interpret the result. (Round to three decimal places as needed.)
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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 table shows the shoe size and heights (in.) for 6 men. Shoe size, x Height, y Find the regression equation. ŷ=x+ (Round to three decimal places as needed.) Choose the correct graph below. O A. Height (in.) 75+ 65- 8 Shoe size N O B. Height (in.) 75+ 65+ 8.5 65.0 Shoe size 9.5 66.0 o 11.0 67.0 O C. Height (in.) 75 65 8 Shoe size 12.0 73.0 Q 13.0 71.0 D. Height (in.) 75- 65 13.5 73.0 Shoe size Q o
Find the intercept (b0) for the regression equation for the following values. Round to 3 decimal places. Intercept xi yi 33 180 25 170 50 200 65 172 57 160 27 165

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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=