Run a linear regression analysis on the following data set with y as the response variable.Use at least 3 decimal places in your regression equation.Xy74.264.318.8-2879.7138.937.4-7.868.212.456.59165.5128.179.581.1What is the predicted value of the response variable when the explanatory variable has value 45.3?y =Round to 1 decimal place.

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Answered: Run a linear regression analysis on the…

College Algebra

1st Edition

ISBN:9781938168383

Author:Jay Abramson

Publisher:Jay Abramson

Chapter4: Linear Functions

Section: Chapter Questions

Problem 30PT: For the following exercises, use Table 4 which shows the percent of unemployed persons 25 years or...

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For the following exercises, use Table 4 which shows the percent of unemployed persons 25 years or older who are college graduates in a particular city, by year. Based on the set of data given in Table 5, calculate the regression line using a calculator or other technology tool, and determine the correlation coefficient. Round to three decimal places of accuracy
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?
For the following exercises, consider the data in Table 5, which shows the percent of unemployed in a city ofpeople25 years or older who are college graduates is given below, by year. 41. Based on the set of data given in Table 7, calculatethe regression line using a calculator or othertechnology tool, and determine the correlationcoefficient to three decimal places.
For the following exercises, consider the data in Table 5, which shows the percent of unemployed ina city of people 25 years or older who are college graduates is given below, by year. 40. Based on the set of data given in Table 6, calculate the regression line using a calculator or other technology tool, and determine the correlation coefficient to three decimal places.
Run a regression analysis on the following data set, where y is the final grade in a math class and x is the average number of hours the student spent working on math each week. hours/week (x) Grade (y) 7 66.8 7 56.8 8 69.2 11 67.4 13 77.2 14 86.6 17 86.8 17 84.8 18 98.2 20 100 State the regression equation y=m⋅x+b, with constants accurate to two decimal places? What is the predicted value for the final grade when a student spends an average of 12 hours each week on math? (Round to 1 decimal place) Grade =
Run a regression analysis on the following data set, where yy is the final grade in a math class and xx is the average number of hours the student spent working on math each week. hours/weekx Gradey 4 51.6 5 43 13 82.2 14 90.6 15 89 16 80.4 16 89.4 18 97.2 19 91.6 19 97.6 State the regression equation with constants accurate to 2 decimal places.ˆyy^ = x + What is the predicted value for the final grade when a student spends an average of 11 hours each week on math? Round to 2 decimal places.
Run a regression analysis on the following data set, where yy is the final grade in a math class and xx is the average number of hours the student spent working on math each week. hours/weekx Gradey 5 59 6 54.4 6 56.4 8 59.2 11 68.4 12 78.8 13 75.2 14 89.6 14 89.6 16 87.4 State the regression equation y=m⋅x+by=m⋅x+b, with constants accurate to two decimal places. What is the predicted value for the final grade when a student spends an average of 15 hours each week on math?Grade = Round to 1 decimal place.
Run a regression analysis on the following data set, where yy is the final grade in a math class and xx is the average number of hours the student spent working on math each week. hours/weekx Gradey 5 56 9 67.6 10 72 11 75.4 12 66.8 13 89.2 13 71.2 14 86.6 14 83.6 14 88.6 State the regression equation y=m⋅x+by=m⋅x+b, with constants accurate to two decimal places.What is the predicted value for the final grade when a student spends an average of 15 hours each week on math?Grade = Round to 1 decimal place.

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