What is the regression equation? ŷ = x (Round to three decimal places as needed.) What is the best predicted number of viewers for a television star with a salary of $4 million? million. The best predicted number of viewers for a television star with a salary of $4 million is (Round to one decimal place as needed.) Is the result close to the actual number of viewers, 4.3 million? O A. The result is very close to the actual number of viewers of 4.3 million. B. The result is not very close to the actual number of viewers of 4.3 million. O C. The result is exactly the same as the actual number of viewers of 4.3 million. D. The result does not make sense given the context of the data.

What is the regression equation? ŷ = x (Round to three decimal places as needed.) What is the best predicted number of viewers for a television star with a salary of $4 million? million. The best predicted number of viewers for a television star with a salary of $4 million is (Round to one decimal place as needed.) Is the result close to the actual number of viewers, 4.3 million? O A. The result is very close to the actual number of viewers of 4.3 million. B. The result is not very close to the actual number of viewers of 4.3 million. O C. The result is exactly the same as the actual number of viewers of 4.3 million. D. The result does not make sense given the context of the data.

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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. Determine the regression equation using values you create for x and y for at least 10 pairs of data. Show the regression equation, correlation coefficient, and coefficient of determination. Then switch the x and y values for each data point. Based on that, again show the regression equation, correlation coefficient, and coefficient of determination. Discuss the similarities and differences between the results.
The table gives the amount of money (in dollars) spent on football by a major university. Letting a represent the number of years since 2011, and letting y represent the amount of money spent on football, in thousands of dollars, use the regression capabilities of a graphing calculator to find the equation of the line of best fit. Round values off to the nearest hundredth. Then, use your equation to make the following predictions. Year 2011 Dollars spent on football 178,000 The equation of the line of best fit is: Hint 2012 2013 2014 2015 196,000 211,000 222,000 244,000 Predict the amount of money that will be spent on football in the year 2024. Predict the amount of money that will be spent on football in the year 2043. 2016 284,000
d. Using the regression results reported above, please calculate and interpret the separate effects of being an athlete on college GPA for men and women.
The table gives the amount of money (in dollars) spent on football by a major university. Letting xx represent the number of years since 2008, and letting yy represent the amount of money spent on football, in thousands of dollars, use the regression capabilities of a graphing calculator to find the equation of the line of best fit. Round values off to the nearest hundredth. Then, use your equation to make the following predictions. Year 2008 2009 2010 2011 2012 2013 Dollars spent on football 169,000 197,000 210,000 222,000 245,000 285,000 The equation of the line of best fit is: Hint Predict the amount of money that will be spent on football in the year 2026. $ Predict the amount of money that will be spent on football in the year 2041. $
Suppose Ms. Carr is interested in the relationship between her students' 9th grade math final exam scores and the number of hours they spent studying during the year. She collects information for 15 ninth grade students and uses it to obtain the regression equation, where ?x is the number of hours spent studying during the year and ?̂ is the predicted final exam score. ?̂ =1.48?+75.64 The scatter plot displays her results. What is the predicted ?̂ value when a student spends 13 hours studying? Round your answer to one decimal place. Select the correct interpretation. The above predicted value of ?̂ is the predicted final math test score if a student studies 13 hours during the year. the predicted score of 13 out of 15 students. what any student will score on the final exam if they study at least 13 hours. the math final test score that 13 students beat.
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
Different patients are randomly selected and measured for pulse rate and body temperature. Using technology with x representing the pulse rates and y representing temperatures, we find that the regression equation has a slope of -0.007 and a y-intercept of 95.6. a. What is the equation of the regression line? b. What does the symbol y represent? a. Choose the correct answer below and fill in the answer boxes to complete your choice. (Type integers or decimals. Do not round.) OA. The equation is Inx=+(y. OB. The equation is Iny=( OC. The equation is y=+x OD. The equation is x=+y b. The symbol y represents value of the actual the mean a predicted ▼ C
Interpret the regression results.
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We recorded the pre-statistics course grade (in percent) and introductory statistics course grade (in percent) for 60 community college students. In this data set, no one earned a 90% for the pre-statistics course grade. How could you estimate a student’s introductory statistics course grade if she earned 90% for the pre-statistics course grade? A. Substitute 90 into the regression equation: Predicted introductory statistics course grade = -0.147 + 0.981(90) . B. Substitute the decimal 0.90 into the regression equation: Predicted introductory statistics course grade = -0.147 + 0.981(0.90).