Assume that researchers measure the concussion screening score using a smart phone app, X, and also measure the score by a comprehensive concussion exam by a physician, Y. The scores are reported in the following table. The researchers also report the sX = 9 and sY = 17.34 and the Pearson’s r between X and Y is .764. What is the regression line using X to predict Y?   X Y 8 100 10 113 15 126 22 125 27 115 28 135 30 154

Listed below are systolic blood pressure measurements (in mm Hg) obtained from the same woman. Find the regression equation, letting the fight 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 Left Arm % 102 101 94 80 79 177 172 143 143 143 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.). Given that the systolic blood pressure in the right arm is 90 mm Hg, the best predicted systolic blood pressure in the left arm is mm Hg. (Round to one decimal place as needed) M H N H & C Copyright ©2022 Pearson Education Inc. All rights reserved. | Terms of Use | Privacy Policy | Permissions | Contact Us | a 33 M 0 8 K Vi 1. fio 11 O More (2) { 87°F Next [ insert prt sc 7:46 8/5/2 backspace

The table below gives the number of hours spent unsupervised each day as well as the overall grade averages for seven randomly selected middle school students. Using this data, consider the equation of the regression line, yˆ=b0+b1x, for predicting the overall grade average for a middle school student based on the number of hours spent unsupervised each day. Keep in mind, the correlation coefficient may or may not be statistically significant for the data given. Remember, in practice, it would not be appropriate to use the regression line to make a prediction if the correlation coefficient is not statistically significant. Hours Unsupervised 1 2 3 4 4.5 5 5.5 Overall Grades 98 95 93 90 89 72 69 Table Copy Data Step 2 of 6 :   Find the estimated y-intercept. Round your answer to three decimal places.

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 $6 million. Is the result close to the actual number of viewers, 8.9 million? Use a significance level of 0.05. Salary (millions of $) Viewers (millions) Click the icon to view the critical values of the Pearson correlation coefficient r. 98 3.5 3 7 13 12 13 10 2 6.8 6.3 10.2 8.5 4.4 1.8 2.7 What is the regression equation? y=+x (Round to three decimal places as needed.) What is the best predicted number of viewers for a television star with a salary of $6 million? The best predicted number of viewers for a television star with a salary of $6 million is million. (Round to one decimal place as needed.) Is the result close to the actual number of viewers, 8.9 million? O A. The result is very close to the actual number of viewers of 8.9 million. O B. The…

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 101 100 92 77 77   Left Arm 174 169 145 146 146

The table below gives the number of hours spent unsupervised each day as well as the overall grade averages for seven randomly selected middle school students. Using this data, consider the equation of the regression line, y = bo + bjx, for predicting the overall grade average for a middle school student based on the number of hours spent unsupervised each day. Keep in mind, the correlation coefficient may or may not be statistically significant for the data given. Remember, in practice, it would not be appropriate to use the regression line to make a prediction if the correlation coefficient is not statistically significant. Hours Unsupervised 0.5 1.5 2.5 3 4 4.5 6 Overall Grades 89 86 81 79 72 67 62 Table Copy Data Step 1 of 6: Find the estimated slope. Round your answer to three decimal places.

a ift = The table below gives the age and bone density for five randomly selected women. Using this data, consider the equation of the regression line, bo + b₁x, for predicting a woman's bone density based on her age. Keep in mind, the correlation coefficient may or may not be statistically significant for the data given. Remember, In practice, it would not be appropriate to use the regression line to make a prediction if the correlation coefficient is not statistically significant. tab ** Answer How to enter your answer (opens in new window) Step 2 of 6: Find the estimated y-Intercept. Round your answer to three decimal places. esc 1945 ! 1 q alt a Z ebook x360 ng from any angle. @ 2 W S →>> X # 3 e d C $ 4 C r f Age Bone Density 359 % 5 V t g 36 51 63 66 70 357 328 314 310 Oll A 6 b y hp h & 7 O n u j * 8 N O i m ( 9 k O 100- 4 Tables ctrl { [ Keypad Keyboard Shortcuts Previous step answers Submit Answer D + = 11 : 90 ; ? Copy Data O SEAR Dec 2 Table ] USE YOUR SMARTPHONE FOR…