Intrepetting simple linear regression models. You are examining the relationship

Question

Intrepetting simple linear regression models.

You are examining the relationship between weight and height, with the hypothesis that an individual’s height (x) can somewhat accurately predict the individual’s weight (y). In your dataset, the height values range from 62 inches to 74 inches (mean = 68 inches, SD = 3.5 inches), and the weight values range from 114 to 200 pounds (mean = 151 pounds, SD = 27 pounds).

(a) In R/Python, you calculate estimates for ?0 and ?1. The fitted model is:

where xi is the height of the ith individual. Interpret both parameters in the model in the context of the original problem.

(b) You calculate a second model, using x'i = xi?62, and get the following fitted model:

Interpret the intercept of this model in the context of the original problem.

(c) You calculate a third model, using x*i= xi ? 68, and get the following fitted model:

Interpret the intercept of this model in the context of the original problem.

(d) Which parameterization (i.e. model) do you prefer best and why?

Explanation / Answer

Solution:

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