Answer:
P = 0.4812
Step-by-step explanation:
First, we need to use here two expressions and then do the calculations.
The first one is the conditional probability which is:
P(B|A) = P(A∩B)/P(A) (1)
The second expression to use has relation with the Bayes's theorem which is the following:
P(D|C) = P(C|D)*P(D) / P(C|D)*P(D) + P(C|d)*P(d) (2)
Now, the expression (2) is the one that we will use to calculate the probability of a selected random bicyclist who tests positive for steroids.
So, in this case, we will call C for positive and D that is using steroids and d is the opposite of d, which means do not use steroids.
Then, the probabilities are the following:
P(D) = 8% or 0.08
P(C|D) = 96% or 0.96
P(C|d) = 9% or 0.09
P(d) = 1 - 0.08 = 0.92
With these data, let's replace in expression 2
P(D|C) = 0.96 * 0.08 /0.96 * 0.08 + 0.09*0.92
P(D|C) = 0.0768 / 0.1596
P(D|C) = 0.4812 or 48.12%
Answer:
there is no intercept
Step-by-step explanation:
I dont really know the answer but u can use this app called photomath and it will help
2.3+0.23 = 2.53
2.53+0.023 = 2.553
