The data in the chart shows the maximum and corresponding resting heart rate of a healthy 20-year old man. Fit a regression line to the data. Then find the coefficient of correlation. Finally, use the regression line to predict the maximum heart rate for a resting heart rate of 42, 57 and 78. resting 50 60 70 80 90 maximum 167 170 170 172 176 Choose the correct regression line. O B. y = 157.0x + 0.20 O A. y = 157.0 O C. y = 0.20x - 157.0 O D. y = 0.20x + 157.0 The coefficient of correlation rounded to 3 decimal places is Is the regression line a good fit? O Yes O No The predicted maximum heart rate for a resting heart rate of 42 is (Round to the nearest integer.) The predicted maximum heart rate for a resting heart rate of 57 is (Round to the nearest integer.)

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…

Given that the linear correlation coefficient r is found to be 0.867, what is the proportion of the variation in the left arm measurements that is explained by the relationship between the right and left arm measurements?   Right arm 102 101 94 79 79 Left arm 175 169 182 146 144

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 numbe of stories of six notable buildings in a city. Height, x Stories, y 778 621 519 510 494 473 (a) x = 500 feet (c) x = 318 feet (b) x = 649 feet (d) x = 727 feet 51 47 45 41 38 36 Find the regression equation.

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 $13 million. Is the result close to the actual number of viewers, 5.7 million? Use a significance level of 0.05. 98 Salary (millions of $) Viewers (millions) 14 2 3.2 9.1 4.6 11 11 7 14 1 D 10.8 10.7 6.3 2.9 4.4 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? Critical Values of the Pearson Correlation Coefficient r n α = 0.05 α = 0.01 NOTE: To test H₂: p=0 = + x (Round to three decimal places as needed.) 4 0.950 0.990 against H₁: p‡0, reject Ho 5 0.878 0.959 if the absolute value of r is 6 0.811 0.917 greater than the critical What is the best predicted number of viewers for a television star with a salary of $13 million? The…

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 40inches. Is the result close to the actual weight of 352​pounds? Use a significance level of 0.05.a. Chest size​ (inches) 41 54 44 55 39 51   Weight​ (pounds) 328  528  418  580  296  503   a.What is the regression​ equation?  b. The best predicted weight for a bear with a chest size of 39 inches is _______pounds.   ​

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 gross if its budget is $115 million. Use a significance level of a = 0.05. Budget ($)in Millions Gross ($) in Millions 41 21 114 68 79 51 118 65 9. 61 122 21 15 151 110 119 11 107 56 128 116 101 107 55 105 222 39 22 283 45 Click the icon to view the critical values of the Pearson correlation coefficient r. The regression equation is y%= X. %3D (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 572 ​pounds? Use a significance level of 0.05.   Chest size​ (inches) 46 57 53 41 40 40   Weight​ (pounds) 384 580 542 358 306 320   LOADING... Click the icon to view the critical values of the Pearson correlation coefficient r. What is the regression​ equation?   y=nothing+nothingx ​ (Round to one decimal place as​ needed.)

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 775 619 519 508 491 474  ​(a) x=503 feet ​(b) x=644 feet ​Stories, y 53 47 44 42 39 38   ​(c) x=798 feet ​(d) x=734 feet

Refer to the data set:(-1, 2), (1, 3), (1, 5), (2, 7), (3, 8), (4, 11)Part a: Make a scatter plot and determine which type of model best fits the data.Part b: Find the regression equation.Part c: Use the equation from Part b to determine y when x = 10