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.
If nCk represents the number of ways k parts can be chosen from a pool of n, the probability of interest is the complement of the probability of selecting all good parts.
1 - (167C3)/(170C3) = 42,085/804,440 ≈ 0.0523
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nCk = n!/(k!(n-k)!)
For the square root of a negative number, you would have to get into imaginary numbers. If you haven't learned about it yet, then the answer would be no real solutions. But if you have, here's how to solve it:
First, identify that 9 x 3 = 27. To after taking the square root, you will get 3√3 (Since the square root of 9 is 3 and there's no square root of 3, so leave it in the √)
However, since it is a negative number, you will have to include the letter i in the answer. i represents the imaginary part of it since you can't have a negative number in the square root.
So your answer will look like 3i√3.
August would be the correct answer.
jus look at the graph, the blue and orange r the closest together in august
