E For the bivariate data at right, do the following.(a) Make a scatter plot and find the correlation coefficient.(b) Create a new variable U = VY. Make a scatter plotof X and U, and find the correlation coefficient of X withU. Also find the equation of the regression line of U uponX, and sketch the regression line in the scatter plot.(c) Use the equation of the regression line in part (b) to derive anequation relating Y and X, and sketch the graph of that equation inthe original scatter plot.Y7161025149

Given data, x y 0 1 2 4 6 9 7 16 10 25

Answered: For the bivariate data at right, do the…

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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Chapter 5: Normal Probability Distributions 38. [APPLET] Milk Consumption You are performing a study about weekly per capita milk consumption. A previous study found weekly per capita milk consumption to be normally distributed, with a mean of 48.7 fluid ounces and a standard deviation of 8.6 fluid ounces. You randomly sample 30 people and record the weekly milk consumptions shown below. 30 33 37 48 57 40 45 54 41 43 31 47 65 25 39 53 51 58 52 40 40 46 46 44 48 443 69 61 52 52 45 38 47 47 49 57 a. Draw a frequency histogram to display these data. Use seven classes. Do the consumptions appear to be normally distributed? Explain. b. Find the mean and standard deviation of your sample. c. Compare the mean and standard deviation of your sample with those of the previous study. Discuss the differences. SC
Solve b
How do I go about these two questions followin this asnwer above: B) Ater removing the point with coordinates (2,9), 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).
The accompanying data are the length (in centimeters) and girths (in centimeters) of 12 harbor seals. Find the equation of the regression line. Then construct a scatter plot of the data and draw the regression line. Then use the regression equation to predict the value of y for each of the given x-values, if meaningful. If the x-value is not meaningful to predict the value of y, explain why not. (a)x= 140 cm (b)x= 172 cm (c) x = 164 cm (d) x = 158 cm Click the icon to view the table of lengths and girths. The equation of the regression line is y=x+7 (Round to two decimal places as needed.). 4
The point (9.1,71) is a point on the scatterplot. Draw the graph of the regression line on the scatterplot on the back of this paper using the y-intercept and the point(I = 3,y = 191). Indicate the residual for z = 9.1 by drawing the vertical line between(9.1, 71) and the corresponding point on the regression line. Will the residual be a positive or negative value?(f) Find the value of the residual for x = 9.1.
Find the multiple regression equation with weight as the response variable and the dummy variable of sex and the variable of age as the explanatory variables.
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.)
a. Using the pairs of values for all 10 points, find the equation of the regression line. b. After removing the point with coordinates (2,3), 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).
Using the weights (Ib) and highway fuel consumption amounts (mi/gal) of the 48 cars listed in the accompanying data set, one gets this regression equation: y = 58 9-0.00749x, where x represents weight Complete parts (a) through (d). Click the icon to view the car data. 東 b. What are the specific values of the slope and y-intercept of the regression line? O A. The slope is 58.9 and the y-intercept is 0.007499. B. The slope is -0.00749 and the y-intercept is 58.9. O C. The slope is 58.9 and the y-intercept is -0.00749. O D. The slope is 0.00749 and the y-intercept is 58.9. c. What is the predictor variable? O A. The predictor variable is highway fuel consumption, which is represented by x. B. The predictor variable is weight, which is represented by x. O C. The predictor variable is weight, which is represented by y O D. The predictor variable is highway fuel consumption, which is represented by y. d. Assuming that there is a significant linear correlation between weight and highway fuel…
The table shows the number of goals allowed and the total points earned (2 points for a win, and 1 point for an overtime or shootout loss) by 14 ice hockey teams over the course of a season. The equation of the regression line is y= - 0.558x + 216.186. Use the data to answer the following questions. (a) Find the coefficient of determination, r, and interpret the result. (b) Find the standard error of the estimate, s,, and interpret the result. Goals Allowed, x Points, y 218 212 216 220 257 266 274 200 211 206 216 204 264 244 O 111 106 99 90 86 83 45 105 100 101 94 83 67 68 (a) ? =O (Round to three decimal places as needed.)
An oceanographer measured the length, in meters, of a deepwater wave and its speed, in meters per second. The results are shown in the following table. (a) Find the equation of a linear regression line for the data where wave length is the independent variable, x, and speed is the dependent variable. (Round your numerical values to two decimal places.) y= ? (b) Using the equation from part (a), estimate the speed (in meters per second) of a wave that is 200 m long. (Round your answer to one decimal place.) ? m/s
The accompanying data are the length (in centimeters) and girths (in centimeters) of 12 harbor seals. Find the equation of the regression line. Then construct a scatter plot of the data and draw the regression line. Then use the regression equation to predict the value of y for each of the given x-values, if meaningful. If the x-value is not meaningful to predict the value of y, explain why not. (a) x=140 cm (b) x=172 cm (c) x=164 cm (d) x=158 cm Length, x Girth, y138 106168 130153 116144 105159 126158 119124 103137 103154 121148 111147 106145 110 The equation of the regression line is y=____x + ___

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