Question

The dosage of medicine that a person is prescribed is often determined by the person's weight. The following

computer output and residual plot for the exponential model were provided. Which of the following statements apply
to this transformed model? Check all that apply.
a The residual plot is patterned.
b The model is a good fit.
c The r2 is considered strong.
d The value of 2 is 99.08%.
e The transformed model compares the log of weight to the log of dosage.

Answer 1

The correct statements that apply to the transformed model are: c. The r2 is considered strong. e. The transformed model compares the log of weight to the log of dosage. The slope of the regression line tells us the rate of change in the response variable (dosage) for each unit increase in the predictor variable (weight). The y-intercept tells us the estimated dosage when the weight is zero. The fit of the regression line to the data can be evaluated by examining the residual plot. If the residuals appear random and scattered around zero, it indicates a good fit. If there is a pattern in the residual plot, it suggests that the model may not be a good fit. The largest residual indicates the point with the largest prediction error. It is not necessarily an outlier or influential point.

Step-by-step explanation:

The correct statements that apply to the transformed model are: c. The r2 is considered strong. e. The transformed model compares the log of weight to the log of dosage.

c. The slope of the regression line tells us the rate of change in the response variable (dosage) for each unit increase in the predictor variable (weight). The y-intercept tells us the estimated dosage when the weight is zero.

d. The fit of the regression line to the data can be evaluated by examining the residual plot. If the residuals appear random and scattered around zero, it indicates a good fit. If there is a pattern in the residual plot, it suggests that the model may not be a good fit.

e. The largest residual indicates the point with the largest prediction error. It is not necessarily an outlier or influential point.