2nd one is the correct one I think
Part A:
A component is one voter's vote. An outcome is a vote in favour of our candidate.
Since there are 100 voters, we can stimulate the component by using two randon digits from 00 - 99, where the digits 00 - 54 represents a vote for our candidate and the digits 55 - 99 represents a vote for the underdog.
Part B:
A trial is 100 votes. We can stimulate the trial by randomly picking 100 two-digits numbers from 00 - 99. Whoever gets the majority of the votes wins the trial.
Part C:
The response variable is whether the underdog wants to win or not. To calculate the experimental probability, divide the number of trials in which the simulated underdog wins by the total number of trials.
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%
