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 41 inches. Is the result close to the actual weight of 273 pounds? Use a significance level of 0.05. Chest size (inches) Weight (pounds) Click the icon to view the critical values of the Pearson correlation coefficient r. 40 53 38 43 44 58 227 360 153 206 234 414 What is the regression equation? y =+ x (Round to one decimal place as needed.)

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 41 inches. Is the result close to the actual weight of 273 pounds? Use a significance level of 0.05. Chest size (inches) Weight (pounds) Click the icon to view the critical values of the Pearson correlation coefficient r. 40 53 38 43 44 58 227 360 153 206 234 414 What is the regression equation? y =+ x (Round to one decimal place as needed.)

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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he 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 39inches. Is the result close to the actual weight of 126 pounds? Use a significance level of 0.05. Chest size (inches) 44 41 41 55 51 42 Weight (pounds) 213 206 176 309 300 178 Critical Values of the Correlation Coefficient r n α=0.05 α=0.01 NOTE: To test H0: ρ=0 against H1: ρ≠0, reject H0if the absolute value of r is greater than the critical value in the table. 4 0.950 0.990 5 0.878 0.959 6 0.811 0.917 7 0.754 0.875 8 0.707 0.834 9 0.666 0.798 10 0.632 0.765 11 0.602 0.735 12 0.576 0.708 13 0.553 0.684 14 0.532 0.661 15 0.514 0.641 16 0.497 0.623 17 0.482 0.606 18 0.468 0.590 19…
Listed below are systolic blood pressure measurements (in mm Hg) obtained from the same woman. Find the regression equation, letting the right arm blood pressure be the predictor (x) variable. Find the best predicted systolic blood pressure in the left arm given that the systolic blood pressure in the right arm is 85 mm Hg. Use a significance level of 0.05. Right Arm 100 99 93 79 78 P Left Arm 177 170 150 148 148 Click the icon to view the critical values of the Pearson correlation coefficient r |x. (Round to one decimal place as needed.) The regression equation is y = Given that the systolic blood pressure in the right arm is 85 mm Hg, the best predicted systolic blood pressure in the left arm is mm Hg. (Round to one decimal place 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 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 table below shows the heights (in feet) and the number of stories of six notable buildings in a city. Height, x Stories, y Un ne conteui yrapii veIUW. O A. Stories A 60- Height (feet) OO ( 800 (a) Predict the value of y for x = 503. Choose the correct answer below. A. 40 OB. 47 O C. 50 O D. not meaningful (b) Predict the value of y for x = 652. Choose the correct answer below. 774 51 OA. 54 O B. 47 OC. 40 O D. not meaningful (c) Predict the value of y for x = 810. Choose the correct answer below. OA. 54 625 47 OA. 54 OB. 50 OC. 47 O D. not meaningful (d) Predict the value of y for x = 725. Choose the correct answer below. B. 40 ΕΛ 521 45 O B. Stories 60+ 508 41 0 Height (feet) 800 497 38 477…
You generate a scatter plot using Excel. You then have Excel plot the trend line and report the equation and the r2r2 value. The regression equation is reported asy=55.82x+32.43y=55.82x+32.43and the r2=0.3136r2=0.3136.What is the correlation coefficient for this data set?r =
use the sample data to construct a scatterplot. Use the first variable for the x-axis. Based on the scatterplot, what do you conclude about a linear correlation? FORECAST AND ACTUAL TEMPERATURES The table lists actual high temperatures and the high temperatures that were previously forecasted for these same days. The table includes data for ten different days near the author’s home. What does the result suggest about the accuracy of five-day predicted high temperatures?
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Listed below are paired data consisting of movie budget amounts and the amounts that the movies grossed. Find the regression equation, letting the budget be the predictor (x) variable. Find the best predicted amount that a movie will groes f to budget is $100 million. Use a significance level of a 0.05. Budget (S)in Millions Gross (S) in Millions 45 17 114 67 70 49 117 67 3. 62 128 21 11 152 10 103 72 131 121 105 105 51 95 203 24 13 289 48 114 12 Click the icon to view the critical values of the Pearson correlation coefficient r. The regression equation is y= x (Round to one decimal place as needed.)
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 50 inches. Is the result close to the actual weight of 417 pounds? Use a significance level of 0.05. Chest size (inches) Weight (pounds) FClick the icon to view the critical values of the Pearson correlation coefficient r. 49 51 53 61 57 45 D 368 382 420 481 457 287 What is the regression equation? y=+x (Round to one decimal place as needed.) Critical Values of the Pearson Correlation Coefficient r n 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 25 30 35 40 45 50 60 70 80 90 100 n Critical Values of the Pearson Correlation Coefficient r α=0.05 α = 0.01 0.950 0.878 0.811 0.754 0.707 0.666 0.632 0.602 0.576 0.553 0.532 0.514 0.497 0.482 0.468 0.456 0.444 0.396 0.361 0.335 0.312 0.294 0.279 0.254 0.236 0.220 0.207 0.196 α = 0.05 Print 0.990 0.959 0.917 0.875 0.834 0.798 0.765 0.735…
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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 43 inches. Is the result close to the actual weight of 237 pounds? Use a significance level of 0.05. Chest size (inches) 50 54 Weight (pounds) 279 44 54 40 36 D 339 219 292 201 116 × Critical Values of the Pearson Correlation Coefficient r Click the icon to view the critical values of the Pearson correlation coefficient i What is the regression equation? ŷ=+x (Round to one decimal place as needed.) Critical Values of the Pearson Correlation Coefficient r n α = 0.05 α=0.01 NOTE: To test Ho: p=0 4 0.950 0.990 5 0.878 0.959 against H₁: p0, reject Ho if the absolute value of r is 6 0.811 0.917 7 0.754 0.875 greater than the critical value in the table. 8 0.707 0.834 9 0.666 0.798 10 0.632 0.765 11 0.602 0.735 12 0.576 0.708 13 0.553 0.684 14 0.532 0.661 15 0.514 0.641 16 0.497 0.623 17…
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