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 ŷ = 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.

Step-by-step explanation:

The mentioned relationship for the weight, in pounds, of the kitten with respect to time, in weeks, is

Weight of the kitten after 10 weeks

pounds

This modeled equation is based on the observation of the early age of a kitten where the kitten is in its growth period, but in the early stage the growth rate in the weight of the kitten was the same but the growth of any living beings continues till the adult stage. So, after some time, in real life situation, this weekly change in weight will become zero, So, this model is not suitable to measure the weight of the kitten over the larger time period.

Here, t= 10 weeks is nearby the observed time period, so the linearly modeled equation can be used to predict the weight.

Hence, the weight of the kitten after 10 weeks is 16.5 pounds.

the k side

step-by-step explanation:

plese mark mde brainliest!

since we know that the two functions are equal, f (x) = g

(x), therefore when we equate the two equations the result should be similar to

3x = x – 4:

a. f(x) = 3x, g(x) = x – 4

equating the two functions:

3x = x – 4             (correct)

so we now got our answer (a)