Evaluating a regression model: A regression was run to determine if there is a relationship between hoursof TV watched per day (x) and number of situps a person can do (y).The results of the regression were: y = - 0.998 · z + 36.998, with an R-squared value of 0.413449.Assume the model indicates a significant relationship between hours of TV watched and the number ofsitups a person can do. Use the model to predict the number of situps a person who watches 1 hours of TVcan do (to one decimal place).

Regression equation is given as, y = - 0.998x + 36.998

Answered: Evaluating a regression model: A…

Glencoe Algebra 1, Student Edition, 9780079039897, 0079039898, 2018

18th Edition

ISBN:9780079039897

Author:Carter

Publisher:Carter

Chapter4: Equations Of Linear Functions

Section4.6: Regression And Median-fit Lines

Problem 6PPS

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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
Find the mean hourly cost when the cell phone described above is used for 240 minutes.
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.
What is regression analysis? Describe the process of performing regression analysis on a graphing utility.
Can the average rate of change of a function be constant?
A regression was run to determine if there is a relationship between hours of TV watched per day (x) and number of sit-ups a person can do (y). The results of the regression were: y=ax+b a=-1.019 b=39.062 R squared = 0.931225 R= 0.965
A regression was run 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: y=ax+b a=-0.817 b=32.111 r²=0.877969 r=-0.937 Use this to predict the number of situps a person who watches 13.5 hour(s) of TV can do, and please round your answer to a whole number.
A regression was run 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: y=ax+b a=-0.877 b=34.57 r2=0.835396 r=-0.914 Use this to predict the number of situps a person who watches 8 hours of TV can do (to one decimal place)
A regression was run to determine if there is a relationship between hours of TV watched per day (xx) and number of situps a person can do (yy).The results of the regression were:y=ax+b a=-0.629 b=39.045 r2=0.806404 r=-0.898 Use this to predict the number of situps a person who watches 6.5 hour(s) of TV can do, and please round your answer to a whole number.
A regression analysis was performed to determine if there is a relationship between hours of TV watched per day (xx) and number of sit ups a person can do (yy). The results of the regression were: y=ax+b a=-0.962 b=32.772 r2=0.502681 r=-0.709 Use this to predict the number of sit ups a person who watches 7.5 hours of TV can do, and please round your answer to a whole number.
A regression was run 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:y=a+bx b=-0.736 a=32.667 r2=0.576081 r=-0.759 Use this to predict the number of situps a person who watches 6 hours of TV can do.
A regression was run 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: y=ax+b a=-0.698 b=37.226 r2=0.799236 r=-0.894 Use this to predict the number of situps a person who watches 14 hours of TV can do (to one decimal place)

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