The table below gives the completion percentage and interception percentage for five randomly selected NFL quarterbacks. Based on this data, consider the equation of the regression line, yˆ=b0+b1xy^=b0+b1x, for using the completion percentage to predict the interception percentage for an NFL quarterback. Keep in mind, the correlation coefficient may or may not be statistically significant for the data given. Remember, in practice, it would not be appropriate to use the regression line to make a prediction if the correlation coefficient is not statistically significant.
Completion Percentage | 60 | 61 | 62 | 65 | 66 |
---|---|---|---|---|---|
Interception Percentage | 5 | 4.5 | 4 | 3.5 | 1.5 |
Table
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Step 1 of 6 :
Find the estimated slope. Round your answer to three decimal places.
From given sample data,
X | Y | X * Y | X^2 |
60 | 5 | 300 | 3600 |
61 | 4.5 | 274.5 | 3721 |
62 | 4 | 248 | 3844 |
65 | 3.5 | 227.5 | 4225 |
66 | 1.5 | 99 | 4356 |
314 | 18.5 | 1149 | 19746 |
Equation of regression line is Ŷ = a + bX
Where slope = b
b = ( 5 * 1149 - 314 * 18.5 ) / ( 5 * 19746 - ( 314 )2)
= -0.478
The table below gives the completion percentage and interception percentage for five randomly selected NFL quarterbacks....
The table below gives the completion percentage and interception percentage for five randomly selected NFL quarterbacks. Based on this data, consider the equation of the regression line, yˆ=b0+b1x, for using the completion percentage to predict the interception percentage for an NFL quarterback. Keep in mind, the correlation coefficient may or may not be statistically significant for the data given. Remember, in practice, it would not be appropriate to use the regression line to make a prediction if the correlation coefficient...
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The table below gives the age and bone density for five randomly selected women. Using this data, consider the equation of the regression line, yˆ=b0+b1xy^=b0+b1x, for predicting a woman's bone density based on her age. Keep in mind, the correlation coefficient may or may not be statistically significant for the data given. Remember, in practice, it would not be appropriate to use the regression line to make a prediction if the correlation coefficient is not statistically significant. Age 5050 5959...
The table below gives the age and bone density for five randomly selected women. Using this data, consider the equation of the regression line, yˆ=b0+b1xy^=b0+b1x, for predicting a woman's bone density based on her age. Keep in mind, the correlation coefficient may or may not be statistically significant for the data given. Remember, in practice, it would not be appropriate to use the regression line to make a prediction if the correlation coefficient is not statistically significant. Age 39 41...
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The table below gives the age and bone density for five randomly selected women. Using this data, consider the equation of the regression line, yˆ=b0+b1x, for predicting a woman's bone density based on her age. Keep in mind, the correlation coefficient may or may not be statistically significant for the data given. Remember, in practice, it would not be appropriate to use the regression line to make a prediction if the correlation coefficient is not statistically significant. Age 39 47...
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