Answer: First of all, we will add the options.
A. Yes, because 3 inches falls above the maximum value of lengths in the sample.
B. Yes, because the regression equation is based on a random sample.
C. Yes, because the association between length and weight is positive.
D. No, because 3 inches falls above the maximum value of lengths in the sample.
E. No, because there may not be any 3-inch fish of this species in the pond.
The correct option is D.
Step-by-step explanation: It would not be appropriate to use the model to predict the weight of species that is 3 inches long because 3 inches falls above the maximum value of lengths in the sample.
As we can see from the question, the model only accounts for species that are within the range of 0.75 to 1.35 inches in length, and species smaller or larger than that length have not been taken into consideration. Therefore the model can not be used to predict the weights of fishes not with the range accounted for.
So to fine slope you would use the formula down below:
rise/run
So use a graphed point, 0, -5 and you rise or count up quadrants up to a point and then horizontally move to when you find that point.
So from 0,-5 go up 9 vertically, and you would be on the 4
Go horizontal 3 spots and your on a designated point.
So the rise is four and the run is 3
So 4/3 is the slope
In the y= Mx + b equation you would set the equation like this:
y= 4/3 + -5
The m in this formula stands for the slop and the b stands for the y-intercept
The y-intercept is the point that is on the y-axis and where it starts.
I believe it is 8,459,999,894,000,001
