Critical values of the pearson correlation coefficient rCritical Values of the Pearson Correlation Coefficient rNOTE: To test Ho: p= 0against H,: p 0, reject H,if the absolute value of r isgreater than the criticalvalue in the table.a = 0.05a = 0.0140.9500.9900.8780.9590.8110.91770.7540.87580.7070.8349.0.6660.798100.6320.765110.6020.735120.5760.708130.5530.684140.5320.661150.5140.641160.4970.623170.4820.606180.4680.590190.4560.575PrintDoneCloar allCheck 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 weightof 277 pounds? Use a significance level of 0.05.Chest size (inches)Weight (pounds)505444544036279339219292201116Click the icon to view the critical values of the Pearson correlation coefficient r......What is the regression equation?y = - 229.6 + (10.2) x (Round to one decimal place as needed.)What is the best predicted weight of a bear with a chest size of 43 inches?The best predicted weight for a bear with a chest size of 43 inches is(Round to one decimal place as needed.)pounds.

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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Find the equation of the regression line for the given data. Then construct a scatter plot of the data and draw the regression line. (Each pair of variables has a significant correlation.) Then use the regression equation to predict the value of y for each of the given x-values, if meaningful. The caloric content and the sodium content (in milligrams) for 6 beef hot dogs are shown in the table below. Calories, x Sodium, y 70 190 530 (a) x = 170 calories (c) x = 140 calories (b) x = 100 calories (d) x = 60 calories 160 180 120 130 410 460 340 370 270 Find the regression equation. (Round to three decimal places as needed.)
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 100 mm Hg. Use a significance level of 0.05. Right Arm 102 101 93 80 80 D Left Arm 176 171 140 142 143 Click the icon to view the critical values of the Pearson correlation coefficient r The regression equation is y= 30.0+ 1.4 x. (Round to one decimal place as needed.) Given that the systolic blood pressure in the right arm is 100 mm Hg, the best predicted systolic blood pressure in the left arm is mm Hg. (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 44 inches. Is the result close to the actual weight of 303 pounds? Use a significance level of 0.05. Chest size (inches) Weight (pounds) 50 321 45 221 265 335 307 265 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.) What is the best predicted weight of a bear with a chest size of 44 inches? The best predicted weight for a bear with a chest size of 44 inches is pounds. (Round to one decimal place as needed.) In the sandl alasa da tha adual metali at 202 sAuedal Is the result close to the actual weight of 303 pounds? O A. This result is exactly the same as the actual weight of the bear. O B. This result is very close to the actual weight of the bear. O C. This result 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 51 inches. Is the result close to the actual weight of 585 pounds? Use a significance level of 0.05. Chest size (inches) Weight (pounds) 47 46 49 50 38 48 O 487 496 546 518 397 510 E Click the icon to view the critical values of the Pearson correlation coefficient r. What is the regression equation? y =+x (Round to one decimal place as needed.)
intents d Resource Listed below are foot lengths (mm) and heights (mm) of males. Find the regression equation, letting foot length be the predictor (x) variable. Find the best predicted height of a male with a foot length of 273.1 mm. How does the result compare to the actual height of 1776 mm? Foot Length 282.4 277.9 253.4 259.3 279.2 258.2 273.6 262:3 Height 1785.1 1770.9 1676.0 1646.1 1859.0 1710.1 1789.3 1736.9 The regression equation is y=+x. (Round the y-intercept to the nearest integer as needed. Round the slope to two decimal places as needed.) ype here to search Tutoring Help me solve this O i Get more help. C 3¹ ... 99+ 0 LA 6 3 Clear all Check answer 78°F ^®
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 90 mm Hg. Use a significance level of 0.05. Right Arm 103 102 95 79 80 Left Arm 174 168 143 143 144 LOADING... Click the icon to view the critical values of the Pearson correlation coefficient r The regression equation is y=____?+____?x.
Find the regression equation, letting the diameter be the predictor (x) variable. Find the best predicted circumference of a marble with a diameter of 1.8 cm. How does the result compare to the actual circumference of 5.7 cm? Use a significance level of 0.05. Baseball Basketball Golf Soccer Tennis Ping-Pong Volleyball 7.5 21.4 4.0 Diameter Circumference 23.6 23.9 75.1 4.3 22.1 13.5 69.4 7.1 22.3 12.6 67.2 Click the icon to view the critical values of the Pearson correlation coefficient r. The regression equation is y= 0 (Round to five decimal places as needed.) + X.
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 2.3 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) 7.2 8.3 8.8 8.1 9.9 9.8 Weight (kg) 121 195 210 156 250 253
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) 40 53 38 43 44 58 227 360 153 206 234 414 Click the icon to view the critical values of the Pearson correlation coefficient r. 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 58 inches. Is the result close to the actual weight of 672 pounds? Use a significance level of 0.05. Chest size (inches) Weight (pounds) 46 57 53 41 40 40 384 580 542 358 306 320
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 92 80 79 O Left Arm 175 169 182 149 148 E 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 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 $3 million. Is the result close to the actual number of viewers, 7.0 million? Use a significance level of 0.05. Salary (millions of $) Viewers (millions) 99 7 4 9 15 4.1 2.2 1.4 4.4 8.3 8.8 4.9 4.3 = Click the icon to view the critical values of the Pearson correlation coefficient r. Critical Values of the Pearson Correlation Coefficient r What is the regression equation? y=+ x (Round to three decimal places as needed.) Critical Values of the Pearson Correlation Coefficient r a =0.05 0.950 What is the best predicted number of viewers for a television star with a salary of $3 million? a= 0.01 NOTE: To test H p=0 0.990 against H, p#0, reject H, if the absolute value of r is greater than the critical value in the table. 14 The best predicted number of…

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