A 2-column table with 9 rows. The first column is labeled year with entries 1970, 1975, 1980, 1985, 1990, 1995, 2000, 2005, 2010
1 answer:
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Answer:
93.25% probability that they have taken this steroid
Step-by-step explanation:
Bayes Theorem:
Two events, A and B.
In which P(B|A) is the probability of B happening when A has happened and P(A|B) is the probability of A happening when B has happened.
In this question:
Event A: Positive test
Event B: Taking the steroid.
Suppose the probability of an athlete taking a certain illegal steroid is 10%.
This means that
Given that the athlete has taken this steroid, the probability of a positive test result is 0.995.
This means that
Positive test:
99.5% of 10%(If the athlete has taken).
100-99.2 = 0.8% of 100-10 = 90%(Athlete has not taken)
Then
Given that a positive test result has been observed for an athlete, what is the probability that they have taken this steroid
93.25% probability that they have taken this steroid
Answer:
Step-by-step explanation:
Given is the probability distribution of a random variable X
X 4 5 6 7 Total
P 0.2 0.4 0.3 0.1 1
x*p 0.8 2 1.8 0.7 5.3
x^2*p 3.2 10 10.8 4.9 28.9
a) E(X) = Mean of X = sum of xp = 5.3
Std dev = square root of variance = 0.9
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b) For sample mean we have
Mean = 5.3
Variance = var(x)/n =
c)