Range of ankle motion is a contributing factor to falls among the elderly. Suppose a team of researchers is studying how compression hosiery, typical shoes, and medical shoes affect range of ankle motion. In particular, note the variables Barefoot and Footwear2. Barefoot represents a subject's range of ankle motion (in degrees) while barefoot, and Footwear2 represents their range of ankle motion (in degrees) while wearing medical shoes. Use this data and your preferred software to calculate the equation of the least-squares linear regression line to predict a subject's range of ankle motion while wearing medical shoes, ?̂ , based on their range of ankle motion while barefoot, ? . Round your coefficients to two decimal places of precision. ?̂ = A physical therapist determines that her patient Jan has a range of ankle motion of 7.26°7.26° while barefoot. Predict Jan's range of ankle motion while wearing medical shoes, ?̂ . Round your answer to two decimal places. ?̂ = Suppose Jan's actual range of ankle motion while wearing medical shoes is 9.79°9.79°. Use her predicted range of ankle motion to calculate the residual associated with this value. Round your answer to two decimal places. residual= In order to assess the linear regression equation's ability to predict range of ankle motion, the physical therapist reviewed a scatterplot of the researchers' sample data and calculated the correlation, ?=0.77. Is it reasonable for the physical therapist to assume that the least-squares linear regression line would accurately predict Jan's range of ankle motion? A) No, because the sample data points do not all fall in a straight line pattern. B) Yes, because the sample data does not contain outliers.
In particular, note the variables Barefoot and Footwear2. Barefoot represents a subject's range of ankle motion (in degrees) while barefoot, and Footwear2 represents their range of ankle motion (in degrees) while wearing medical shoes.
Use this data and your preferred software to calculate the equation of the least-squares linear regression line to predict a subject's range of ankle motion while wearing medical shoes, ?̂ , based on their range of ankle motion while barefoot, ? . Round your coefficients to two decimal places of precision.
?̂ =
A physical therapist determines that her patient Jan has a range of ankle motion of 7.26°7.26° while barefoot. Predict Jan's range of ankle motion while wearing medical shoes, ?̂ . Round your answer to two decimal places.
?̂ =
Suppose Jan's actual range of ankle motion while wearing medical shoes is 9.79°9.79°. Use her predicted range of ankle motion to calculate the residual associated with this value. Round your answer to two decimal places.
residual=
In order to assess the linear regression equation's ability to predict range of ankle motion, the physical therapist reviewed a
Is it reasonable for the physical therapist to assume that the least-squares linear regression line would accurately predict Jan's range of ankle motion?
A) No, because the sample data points do not all fall in a straight line pattern.
B) Yes, because the sample data does not contain outliers.
C) Yes, because the ranges of ankle motion follow a linear pattern and ? is close to 1.
D) No, because the prediction can only be accurate if the correlation, ?, is greater than 0.850.85 or less than −0.85−0.85.
E) No, because coefficient of determination R-square is relatively small.
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