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 | 45 | 49 | 61 | 65 | 71 |
---|---|---|---|---|---|
Bone Density | 356 | 355 | 350 | 340 | 312 |
Step 1 of 6 :
Find the estimated slope. Round your answer to three decimal places.
Step 2 of 6 :
Find the estimated y-intercept. Round your answer to three decimal places.
Step 3 of 6 :
Determine the value of the dependent variable y^ at x=0.
A. B0
B. B1
C. X
D. Y
Step 4 of 6:
True or False:
All the points fall in a straight line
Step 5 of 6 :
According to the estimated linear model, if the value of the independent variable is increased by one unit, then the change in the dependent variable y^ is given by?
A. B0
B. B1
C. X
D. Y
Step 6 of 6 :
Find the value of the coefficient of determination. Round your answer to three decimal places.
from above
Step 1 of 6 : estimated slope =-1.425
Step 2 of 6 : estimated y-intercept =425.555
Step 3 of 6 : A. B0
Step 4 of 6: true
Step 5 of 6 : B. B1
Step 6 of 6 :
SST=Syy= | 1,331.2000 | |
SSE =Syy-(Sxy)2/Sxx= | 362.5419 | |
SSR =(Sxy)2/Sxx = | 968.6581 |
Coeffficient of determination R^2 =SSR/SST= | 0.728 |
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