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:
3x+7=10x+17
Step-by-step explanation:
1.9
10x
27x
Answer:
-There is an outlier at (4.5,15).
-The point (2,60) is an outlier, because it is far away from the rest of the points.
Step-by-step explanation:
An outlier is a data point that is far away from the rest of the data. An outlier does not necessarily represent the extremes in a set of data, as long as it is close to the other points. So, based on the scatter plot, there are two outliers at (2,60) and (4.5,15).
The following statements are true.
There is an outlier at (4.5,15).
The point (2,60) is an outlier because it is far away from the rest of the points.