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The weight, y, in pounds, of puppies was tracked for the first 10 weeks after birth, where t represents the number of weeks after birth.
The weight, y, in pounds, of puppies was tracked for the first 10 weeks after birth, where t represents the number of weeks after birth. The linear model representing this relationship is y hat equals 2.3 plus 5.73 times t. Diandra wanted to predict the weight of a puppy at 14 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 14 weeks is outside the given interval of 10 weeks. This is an example of extrapolation. Extrapolation is not a best practice for prediction, as the prediction is not accurate because 14 weeks is outside the given interval of 10 weeks. This is an example of linear modeling. Linear modeling is a best practice for prediction, as the prediction is accurate even though 14 weeks is outside the given interval of 10 weeks. This is an example of linear modeling. Linear modeling is not a best practice for prediction, as the prediction is not accurate because 14 weeks is outside the given interval of 10 weeks
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