plain in simple language why knowing only these correlations enables you to say that prediction of manatee deaths from number of boats registered by a regression line will be much more accurate than prediction of a golfer's second‑round score from his first‑round score. Select the correct explanation from the choices.   A) The closer r is to 0 (in either direction), the stronger the linear relationship is between two variables.   B) Actually, prediction of manatee deaths from number of boats registered by a regression line will be much less accurate than prediction of a golfer's second‑round score from his first‑round score.   C) The fraction of the variation in the observed values of x explained by the least‑squares regression of y on x is given by r. The higher this fraction, the more likely that the prediction is accurate.   D) The further r is from 0 (in either direction), the stronger the linear relationship is between two

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    Bone Density34    35745    34148    33160    32965    325 Step 2 of 6:  Find the estimated y-intercept. Round your answer to three decimal places.

The table below gives the number of hours seven randomly selected students spent studying and their corresponding midterm exam grades. Using this data, consider the equation of the regression line, yˆ=b0+b1x, for predicting the midterm exam grade that a student will earn based on the number of hours spent studying. 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. Hours Studying 1 1.5 2 2.5 3 3.5 4.5 Midterm Grades 61 62 75 77 79 83 88 Table   Step 1 of 6 :  Find the estimated slope, y intercept and correlation cofficient. Round your answer to three decimal places.

If the estimated intercept of the regression equation is negative, we can say the estimated correlation coefficient between the two variables is also negative. O True O False

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 43 46 61 64 Bone Density 352 346 321 314 312 Table   Step 1 of 6 :  Find the estimated slope. Round your answer to three decimal places

Can you please check my work

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 50 59 60 64 68 Bone Density 331 326 325 320 315 Table   Step 3 of 6 :  Substitute the values you found in steps 1 and 2 into the equation for the regression line to find the estimated linear model. According to this model, if the value of the independent variable is increased by one unit, then find the change in the dependent variable yˆ.

In a fisheries researchers experiment the correlation between the number of eggs in tge nest and the number of viable (surviving ) eggs for a sample of nests is r=0.67  the equation of the regression line for number of viable eggs y versus number of eggs in the nest x is y =0.72x + 17.07 for a nest with 140 eggs what is the predicted number of viable eggs ?

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 50 59 60 64 68 Bone Density 331 326 325 320 315 Table   Step 1 of 6 :  Find the estimated slope, y instercept and correlation coefficient. Round your answers to three decimal places.