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The weight, y, in pounds, of human babies was tracked for the first 12 weeks after birth, where t represents the number of weeks after birth. The linear model representing this relationship is y = 6.7 +0.52t. Douglas wanted to predict the weight of a baby at 16 weeks. What is this an example of, and is this method a best practice for prediction? Explain your reasoning.

The weight, y, in pounds, of human babies was tracked for the first 12 weeks after birth, where t represents the number of weeks after birth. The linear model representing this relationship is y = 6.7 +0.52t. Douglas wanted to predict the weight of a baby at 16 weeks. What is this an example of, and is this method a best practice for prediction? Explain your reasoning.

A First Course in Probability (10th Edition)
A First Course in Probability (10th Edition)
10th Edition
ISBN:9780134753119
Author:Sheldon Ross
Publisher:Sheldon Ross
Chapter1: Combinatorial Analysis
Section: Chapter Questions
Problem 1.1P: a. How many different 7-place license plates are possible if the first 2 places are for letters and...
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This is a probability and statistics math class. Please help me get this correct so I can study.
The weight, y, in pounds, of human babies was tracked for the first 12 weeks after birth, where t represents the number of weeks after birth. The linear model representing this relationship is ý = 6.7 +0.52t. Douglas wanted to predict the weight of a baby at 16 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 not a best practice for prediction, as the prediction is not accurate because 16 weeks is outside the given interval of 12 weeks. O This is an example of extrapolation. Extrapolation is a best practice for prediction, as the prediction is accurate even though 16 weeks is outside the given interval of 12 weeks. This is an example of linear modeling. Linear modeling is a best practice for prediction, as the prediction is accurate even though 16 weeks is outside the given interval of 12 weeks. O This is an example of linear modeling. Linear modeling is not a best practice for prediction, as the prediction is not accurate because 16 weeks is outside the given interval of 12 weeks.
Transcribed Image Text:The weight, y, in pounds, of human babies was tracked for the first 12 weeks after birth, where t represents the number of weeks after birth. The linear model representing this relationship is ý = 6.7 +0.52t. Douglas wanted to predict the weight of a baby at 16 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 not a best practice for prediction, as the prediction is not accurate because 16 weeks is outside the given interval of 12 weeks. O This is an example of extrapolation. Extrapolation is a best practice for prediction, as the prediction is accurate even though 16 weeks is outside the given interval of 12 weeks. This is an example of linear modeling. Linear modeling is a best practice for prediction, as the prediction is accurate even though 16 weeks is outside the given interval of 12 weeks. O This is an example of linear modeling. Linear modeling is not a best practice for prediction, as the prediction is not accurate because 16 weeks is outside the given interval of 12 weeks.
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