The table below gives the age and bone density for five randomlyselected women. Using this data, consider the equation of theregression line, yˆ=b0+b1x', for predicting a woman's bone densitybased on her age. Keep in mind, the correlation coefficient may ormay not be statistically significant for the data given. Remember,in practice, it would not be appropriate to use the regression lineto make a prediction if the correlation coefficient is notstatistically significant.
| Age | 40 | 41 | 42 | 43 | 63 |
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| Bone Density | 353 | 344 | 328 | 326 | 322 |
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Table
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Step 1 of 6:
Find the estimated slope. Round your answer to three decimalplaces.
Step 2 of 6:
Find the estimated y-intercept. Round your answer to threedecimal places.
Step 3 of 6:
Determine if the statement "Not all points predicted by thelinear model fall on the same line" is true or false.
Step 4 of 6:
Substitute the values you found in steps 1 and 2 into theequation for the regression line to find the estimated linearmodel. According to this model, if the value of the independentvariable is increased by one unit, then find the change in thedependent variable yˆ.
Step 5 of 6:
Find the estimated value of y when x=42. Round your answer tothree decimal places.
Step 6 of 6:
Find the value of the coefficient of determination. Round youranswer to three decimal places.
