The table below gives the age and bone density for five randomly selected women. Using this data, consider the equation of the regression line, y = bo + bịx, 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 47 49 50 51 58 Bone Density 360 353 336 333 310 Table Copy Data Step 2 of 6: Find the estimated y-intercept. Round your answer to three decimal places.

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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, y = bo + bịx, 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
47
49
50
51
58
Bone Density
360
353
336 333
310
Table
Copy Data
Step 2 of 6: Find the estimated y-intercept. Round your answer to three decimal places.
Transcribed Image Text:The table below gives the age and bone density for five randomly selected women. Using this data, consider the equation of the regression line, y = bo + bịx, 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 47 49 50 51 58 Bone Density 360 353 336 333 310 Table Copy Data Step 2 of 6: Find the estimated y-intercept. Round your answer to three decimal places.
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