## Consider the dataset ape::carnivora.
## From the variable BW, remove out any observations smaller than
## 0.01.
## Fit multiple linear regression, predicting BW with GL and
## SuperFamily.
## Write the fitted regression equation.
## Translate an intercept in context.
## Translate the slope in context.
## What value of the response does the above model predict for a
## member of the super family Feliformia that has a gestation length
## of 59?
## Calculate the residual for a member of Feliformia that has a
## gestation length of 59 and weights 20 grams at birth.
## Calculate the fitted values and standardized residuals.
## With plots, check the assumptions on multiple linear regression.
## Fit multiple linear regression, predicting log(BW) with log(GL) and SuperFamily.
## Write the fitted regression equation.
## Translate an intercept in context.
## Translate the slope in context.
## What value of the response does the above model predict for a
## member of the super family Feliformia that has a gestation length
## of 59?
## Calculate the residual for a member of Feliformia that has a
## gestation length of 59 and weights 20 grams at birth.
## Calculate the fitted values and standardized residuals.
## With plots, check the assumptions on multiple linear regression.
## Compare your two fitted models. Note which assumptions seem more
## important and why. Is there any grand theorem we have that allows
## us to tolerate irregularities in a particular assumption?