A researcher studied the relationship between stress test scores (x variable) and blood pressure (y variable) and determined the linear regression equation is y= 72.5 + 23.7x. He also found the sample correlation coefficient r=0.956. Using the equation of the line we can predict a person with a stress test score of 7 will have a blood pressure of type your answer... the nearest whole number. The interpretation of the slope in the context of the problem is: type your answer.... The interpretation of the y-intercept in the context of the problem is: type your answer... appropriate". Round your final answer to If it is not appropriate to interpret the y-intercept answer "Not The percentage of the variation in the blood pressure that can be explained by the stress test score is type your answer.... rounded to the nearest whole number. %. Write your answer as a percentage s

A researcher studied the relationship between stress test scores (x variable) and blood pressure (y variable) and determined the linear regression equation is y= 72.5 + 23.7x. He also found the sample correlation coefficient r=0.956. Using the equation of the line we can predict a person with a stress test score of 7 will have a blood pressure of type your answer... the nearest whole number. The interpretation of the slope in the context of the problem is: type your answer.... The interpretation of the y-intercept in the context of the problem is: type your answer... appropriate". Round your final answer to If it is not appropriate to interpret the y-intercept answer "Not The percentage of the variation in the blood pressure that can be explained by the stress test score is type your answer.... rounded to the nearest whole number. %. Write your answer as a percentage s

Functions and Change: A Modeling Approach to College Algebra (MindTap Course List)

6th Edition

ISBN:9781337111348

Author:Bruce Crauder, Benny Evans, Alan Noell

Publisher:Bruce Crauder, Benny Evans, Alan Noell

Chapter3: Straight Lines And Linear Functions

Section3.4: Linear Regression

Problem 12SBE: Find the equation of the regression line for the following data set. x 1 2 3 y 0 3 4

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Find the equation of the regression line for the following data set. x 1 2 3 y 0 3 4
Does Table 1 represent a linear function? If so, finda linear equation that models the data.
Olympic Pole Vault The graph in Figure 7 indicates that in recent years the winning Olympic men’s pole vault height has fallen below the value predicted by the regression line in Example 2. This might have occurred because when the pole vault was a new event there was much room for improvement in vaulters’ performances, whereas now even the best training can produce only incremental advances. Let’s see whether concentrating on more recent results gives a better predictor of future records. (a) Use the data in Table 2 (page 176) to complete the table of winning pole vault heights shown in the margin. (Note that we are using x=0 to correspond to the year 1972, where this restricted data set begins.) (b) Find the regression line for the data in part ‚(a). (c) Plot the data and the regression line on the same axes. Does the regression line seem to provide a good model for the data? (d) What does the regression line predict as the winning pole vault height for the 2012 Olympics? Compare this predicted value to the actual 2012 winning height of 5.97 m, as described on page 177. Has this new regression line provided a better prediction than the line in Example 2?
The regression equation for for the association between BMI and total cholesterol level is: y = 28.07 + 6.49x A.) Suppose a participant has a BMI of 26. What would we estimate the total cholesterol to be? B.) Suppose two individuals have a mean BMI that differs by 3 units. What is the estimated difference in total cholesterol. C.) What ranges of BMI should the equation be used to predict total cholesterol?
Please show how you came to your answer.
A regression was run using 11 subjects to determine if there is a relationship between hours of TV watched per day (x) and number of situps a person can do (y).The results of the regression were: Regression Equation....... y=b0+b1xy=b0+b1x Slope..................... b1=−1.282b1=-1.282 y-Intercept............... b0=38.871b0=38.871 Sample size............... n=11n=11 Correlation Coefficient... r=−0.79r=-0.79 Use this to predict the number of situps a person who watches 1 hours of TV can do (to one decimal place)
The accompanying data are the number of wins and the earned run averages (mean number of earned runs allowed per nine innings pitched) for eight baseball pitchers in a recent season. Find the equation of the regression line. Then construct a scatter plot of the data and draw the regression line. Then use the regression equation to predict the value of y for each of the given x-values, if meaningful. If the x-value is not meaningful to predict the value of y, explain why not. (a) x= 5 wins E Click the icon to view the table of numbers of wins and earned run average. (b) x = 10 wins (c) x = 19 wins (d) x= 15 wins ..... The equation of the regression line is y = x+O (Round to two decimal places as needed.) Wins and ERA Earned run Wins, x average, y 20 2.71 18 3.19 17 2.69 16 3.68 14 3.94 12 4.25 11 3.86 9 5.18 Print Done
The accompanying data are the number of wins and the earned run averages (mean number of earned runs allowed per nine innings pitched) for eight baseball pitchers in a recent season. Find the equation of the regression line. Then construct a scatter plot of the data and draw the regression line. Then use the regression equation to predict the value of y for each of the given x-values, if meaningful. If the x-value is not meaningful to predict the value of y, explain why not. (a) x = 5 wins E Click the icon to view the table of numbers of wins and earned run average. (b) x = 10 wins (c) x = 19 wins (d) x = 15 wins The equation of the regression line is y =x+. (Round to two decimal places as needed.) Enter your answer in the edit fields and then click Check Answer. Check Answer Clear All 5 parts remaining
The accompanying data are the number of wins and the earned run averages (mean number of earned runs allowed per nine innings pitched) for eight baseball pitchers in a recent season. Find the equation of the regression line. Then construct a scatter plot of the data and draw the regression line. Then use the regression equation to predict the value of y for each of the given x-values, if meaningful. If the x-value is not meaningful to predict the value of y, explain why not. Wins, x 20 18 17 16 14 12 11 9 Earned run average, y 2.83 3.34 2.61 3.79 3.94 4.37 3.76 5.15 The equation of the regression line is ŷ = ______ x + ______ (Round the slope to three decimal places as needed. Round the y-intercept to two decimal places as needed.) (a) x = 5 wins, (b) x = 10 wins, (c) x = 19 wins, (d) x = 15 wins Use the regression equation to predict the value of y for each of the above x-values,…
The accompanying data are the number of wins and the earned run averages (mean number of earned runs allowed per nine innings pitched) for eight baseball pitchers in a recent season. Find the equation of the regression line. Then construct a scatter plot of the data and draw the regression line. Then use the regression equation to predict the value of y for each of the given x-values, if meaningful. If the x-value is not meaningful to predict the value of y, explain why not. (a) x=5 wins (b) x=10 wins (c) x=21 wins (d) x=15 wins Wins, x Earned run average, y20 2.7118 3.3117 2.6216 3.8214 3.9512 4.4311 3.739 5.03 Then construct a scatter plot of the data and draw the regression line. (a) Predict the ERA for 5 wins, if it is meaningful. Select the correct choice below and, if necessary, fill in the answer box within…
The accompanying data are the number of wins and the earned run averages (mean number of earned runs allowed per nine innings pitched) for eight baseball pitchers in a recent season. Find the equation of the regression line. Then construct a scatter plot of the data and draw the regression line. Then use the regression equation to predict the value of y for each of the given x-values, if meaningful. If the x-value is not meaningful to predict the value of y, explain why not. (a) x=5 wins (b) x=10 wins (c) x=19 wins (d) x=15 wins wins x average y 20 2.79 18 3.36 17 2.59 16 3.72 14 3.85 12 4.32 11 3.81 9 5.11 The equation of the regression…
The accompanying data are the number of wins and the earned run averages (mean number of earned runs allowed per nine innings pitched) for eight baseball pitchers in a recent season. Find the equation of the regression line. Then construct a scatter plot of the data and draw the regression line. Then use the regression equation to predict the value of y for each of the given x-values, if meaningful. If the x-value is not meaningful to predict the value of y, explain why not. (a) x = 5 wins (c) x = 19 wins (d) x = 15 wins (b)x= 10 wins Click the icon to view the table of numbers of wins and earned run average. .. The equation of the regression line is y=x+ X+ (Round to two decimal places as needed.) Construct a scatter plot of the data and draw the regression line. Choose the correct graph below. OA. B. O C. O D. AERA AERA 6+ Q AERA 6+ 4- 4- 2- 2- 0- 6 12 18 24 0 12 18 24 6 12 18 24 Wins 12 18 24 Wins Wins Wins (a) Predict the ERA for 5 wins, if it is meaningful. Select the correct…