The scatter plot shows the relationshipbetween two variables, along with theresults of a linear regression. Whathappens if the outlier is removed?30-25-2015-010-5-12367X-y = 2.08x + 2.5; r² = 0.49OA)The line of best fit will slope moresteeply.The coefficient of determinationB)will decrease.5 2520151050012367X-y = 2.08x +2.5; r² = 0.49OA)The line of best fit will slope moresteeply.B)The coefficient of determinationwill decrease.O CThe line of best fit will slope lesssteeply.D)The line of best fit will slope lesssteeply and the coefficient ofdetermination will decrease.0O55

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Answered: The scatter plot shows the relationship…

Advanced Engineering Mathematics

10th Edition

ISBN:9780470458365

Author:Erwin Kreyszig

Publisher:Erwin Kreyszig

Chapter2: Second-order Linear Odes

Section: Chapter Questions

Problem 1RQ

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Using the data, run a regression where you control for “Promotion,” and test the effect of “Wins” on “Attendance”. What should be the attendance if the number of wins is 10? Wins Promotion Attendance 4 29500 36300 6 55700 40100 6 71300 41200 8 87000 53000 6 75000 44000 7 72000 45600 5 55300 39000 7 81600 47500
6, 5. Kathy painted a picture and posted it on a social media site. The table shows the number of people who responded that they liked the picture since Kathy posted it. Time Since Picture Was Posted 5. 7. (days) Number of Likes 11 21 38 Write the regression equation that best models the data. a. y = 0.96(1. 55)* b. y = 2.07(1. 38)* c. y = 0.536x – 0.857x + 1.81 d. y = 1.38x´ + 0.30x + 0. 43
Interpret the regression results.
Develop a scatterplot and explore the correlation between customer age and net sales by each type of customer (regular/promotion). Use the horizontal axis for the customer age to graph. Find the linear regression line that models the data by each type of customer. Round the rate of changes (slopes) to two decimal places and interpret them in terms of the relation between the change in age and the change in net sales. What can you conclude? Hint: Rate of Change = Vertical Change / Horizontal Change = Change in y / Change in x
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…
The data shows the scores of 8 employees in an admission test and their academic performance. 1. Trace the regression line 2. What is the slope of the line? 3. What is the y-intercept? Score in admission test (x) 52 Grade (y) 80 61 79 86 79 45 95 90 75 58 82 60 80 45 70
A social scientist collects information about counties in California and finds that the correlation between average income of the county and a rating of healthcare quality in the county is 0.78. A scatterplot of the two variables is football shaped. A particular county has an average income that is 0.4 SDs above the average of all counties. Using regression, we would predict that its healthcare quality is _________ SDs above the average healthcare quality for all counties, and that it is therefore at the _________ percentile of healthcare quality among all counties. Choose the answer below to fill in the two blanks. Group of answer choices 0.31; 24th 0.78; 58th 0.78; 79th 0.31; 62nd PreviousNext
What is the explanatory variable, what is the response variable. What is the regression equation for this data. Plot the regression line in your calculator and draw it on your graph. Interpret in context the slope. Interpret in context the y-intercept. What is the residual at 45 years of age. Plot the residual plot on the axis to the right

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The scatter plot shows the relationship between two variables, along with the results of a linear regression. What happens if the outlier is removed? 30 25 20 15 10 5 1 2 3 4 5 6 -y=2.08x + 2.5; r² = 0.49 X 7