The Experimental probability would be 1/2 or 50% it goes that way for both, hope that helps
Her home was 2 km 691 m from the store. (5 km = 5000m --> 5000-2309)
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:
see explaination
Step-by-step explanation:
Here the null hypothesis is that the PCB survives against the alternate that the PCB 'does not survive'. The test says that the PCB will survice if it is classified as 'good'; or, it will not survive if it is classifies as 'bad'.
a. The Type II error is the error committed when a PCB which cannot actually survive is classified as 'good'.
b. Therefore P(Type II error) = P(The PCB is classified as 'good' | PCB does not survives) = 0.03.
we are given the probability that is 88% of person A speaking the truth. The probability of person B speaking the truth on an occasion that person A also speaks the truth is 43%. This means the probability that person A speaks the truth, but person B lies 0.88*(1-0.43) equal to 0.5016