KThe 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 63 inches. Is the result close to the actual weight of 462 pounds? Use asignificance level of 0.05.Chest size (inches)Weight (pounds)584145031265 59499 4505945648 D260CITT

The data set is,Chest Size (inches)585065595948Weight (pounds)414312499450456260

Answered: The data show the chest size and weight…

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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The data show the number of viewers for television stars with certain salaries. Find the regression equation, letting salary be the independent (x) variable. Find the best predicted number of viewers for a television star with a salary of $7 million. Is the result close to the actual number of viewers, 5.2 million? Use a significance level of 0.05. Salary (millions of $) 108 14 5 8 5.1 4.3 7.8 2.5 Viewers (millions) Click the icon to view the critical values of the Pearson correlation coefficient r. What is the regression equation? y=+x (Round to three decimal places as needed.) X 1 1 5 8 5.7 8.2 10.9 4.4
Interpret the regression results.
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 51 inches. Is the result close to the actual weight of 4 punds? Use a significance level of 0.05. thest size (inches) Veight (pounds) Click the icon to view the critical values of the Pearson correlation coefficient r. 45 43 43 52 52 352 374 275 314 440 367 Critical Values of the Pearson Correlation Coefficient r What is the regression equation? Critical Values of the Pearson Correlation Coefficient r a = 0.05 NOTE: To test Ho: p=0 against H, p#0, reject Ho if the absolute value of r is greater than the critical value in the table. y%3= x (Round to one decimal place as needed.) a = 0.01 4 0.950 0.990 0.878 0.959 0.811 0.917 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 0.606 0.590…
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. 483 Height, x Stories, y 772 628 518 508 51 48 45 42 496 37 (a) x=499 feet (c) x=315 feet (b)x=639 feet (d) x = 732 feet 35 Find the regression equation. ŷ=x+ (Round the slope to three decimal places as needed. Round the y-intercept to two decimal places as needed.) Choose the correct graph below. O C. OB. O D. OA. Q Q ↓ 0 0 Height (feet) Height (feet) (a) Predict the value of y for x = 499. Choose the correct answer below. OA. 51 OB. 40 60+ 0- 800 60+ 0- 800 Q A 60- → 0 Height (feet) 800 60- 0- 800 0 Height (feet)
Find the regression equation, letting the diameter be the predictor (x) variable. Find the best predicted circumference of a marble with a diameter of 1.9 cm. How does the result compare to the actual circumference of 6.0 cm? Use a significance level of 0.05. Baseball Basketball Golf Soccer Tennis Ping-Pong Volleyball 5 Diameter 7.4 23.6 4.3 21.7 7.1 3.9 21.5 Circumference 23.2 74.1 13.5 68.2 22.3 12.3 67.5
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 153 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 D 227 360 153 206 234 414 What is the regression equation? y=+x (Round to one decimal place as needed.) What is the best predicted weight of a bear with a chest size of 41 inches? The best predicted weight for a bear with a chest size of 41 inches is (Round to one decimal place as needed.) Is the result close to the actual weight of 153 pounds? O A. This result is exactly the same as the actual weight of the bear. O B. This result is close to the actual weight of the bear. O C. This result is very close to the actual weight of the bear. O D. This…
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 392 pounds? Use a significance level of 0.05. Chest size (inches) Weight (pounds) E Click the icon to view the critical values of the Pearson correlation coefficient r. 41 54 44 55 39 51 328 528 418 580 296 503 ..... What is the regression equation? y =+x (Round to one decimal place as needed.) What is the best predicted weight of a bear with a chest size of 40 inches? The best predicted weight for a bear with a chest size of 40 inches is pounds. (Round to one decimal place as needed.) Is the result close to the actual weight of 392 pounds? O A. This result is close to the actual weight of the bear. O B. This result is exactly the same as the actual weight of the bear. O C. This result is very close to the actual weight of the…
Find the regression equation, letting overhead width be the predictor (x) variable. Find the best predicted weight of a seal if the overhead width measured from a photograph is 2.5 cm. Can the prediction be correct? What is wrong with predicting the weight in this case? Use a significance level of 0.05. Overhead Width (cm) 7.6 7.4 9.8 8.8 9.3 7.3 Weight (kg) 142 163 256 188 231 156 The regression equation is y= + x. (Round to one decimal place as needed.) The best predicted weight for an overhead width of 2.5 cm is kg? (Round to one decimal place as needed.) Can the prediction be correct? What is wrong with predicting the weight in this case? A. The prediction cannot be correct because a negative weight does not make sense. The width in this case is beyond the scope of the available sample data. B. The prediction cannot be correct because a negative weight does not make sense and because there is…
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 48 inches. Is the result close to the actual weight of 308 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. 58 49 58 43 46 57 355 266 332 177 246 348 What is the regression equation? y = + x (Round to one decimal place as needed.) %3D What is the best predicted weight of a bear with a chest size of 48 inches? The best predicted weight for a bear with a chest size of 48 inches is pounds. (Round to one decimal place as needed.) Is the result close to the actual weight of 308 pounds? A. This result is not very close to the actual weight of the bear. B. This result is close to the actual weight of the bear. C. This result is exactly the same as the actual weight of the bear.…

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