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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 $2 million. Is the result close to the actual number of viewers, 4.1 million? Use a significance level of 0.05. Salary (millions of $) Viewers (millions) 101 5.5 7.4 6.8 4.7 12 6.6 2.3 8.1 Click the icon to view the critical values of the Pearson correlation coefficient r. What is the regression equation? y=[+ *(Round to three decimal places as needed.) i Critical Values of the Pearson Correlation Coefficient r - X What is the best predicted number of viewers for a television star with a salary of $2 million? The best predicted number of viewers for a television star with a salary of $2 million is ] million. Critical Values of the Pearson Correlation Coefficient r (Round to one decimal place as needed.) 1 = 0.05 X = 0.01 NOTE: To test Ho: p= 0 0.950 0.980 against H,: p =0. reject Ho Is the result close to the actual number of viewers, 4.1 million? 0.878 0.959 if the absolute value of r is 0.811 0.917 greater than the critical O A. The result is not very close to the actual number of viewers of 4.1 million. 0.754 0.875 value in the table. 0.707 0.834 O B. The result is very close to the actual number of viewers of 4.1 million. 0.666 0.798 O C. The result is exactly the same as the actual number of viewers of 4.1 million. 0.632 0.785 0.602 0.735 O D. The result does not make sense given the context of the data 0.576 0.705 0.553 D.684 0.532 0.681 0.514 D.641 0.497 0.62 0.482 0.606 0.468 0.580 0.456 0.575 0.444 0.581 0.396 0.505 0.361 0.463 0.335 0.430 0.312 0.402 0.294 0.378 0.279 0.381 0.254 0.330 0.236 0.305 0.220 0.286 0.207 0.26 D. 196 0.256 X = 0.05 X = 0.01