The weight, y, in pounds, of kittens was tracked for the first 8 weeks after birth where t represents the number of weeks after birth. The linear model representing this relationship is y = 1.7 + 1.48t. Statler wanted to predict the weight of a kitten at 10 weeks. What is this an example of, and is this method a best practice for prediction? Explain your reasoning. This is an example of extrapolation. Extrapolation is a best practice for prediction as the prediction is accurate even though 10 weeks is outside the given interval of 8 weeks. This is an example of extrapolation. Extrapolation is not a best practice for prediction as the prediction is not accurate because 10 weeks is outside the given interval of 8 weeks. This is an example of linear modeling. Linear modeling is a best practice for prediction as the prediction is accurate even though 10 weeks is outside the given interval of 8 weeks. This is an example of linear modeling. Linear modeling is not a best practice for prediction as the prediction is not accurate because 10 weeks is outside the given interval of 8 weeks. The type of prediction is unable to be determined by the information given