E and F are two events and that P(E)=0.3 and P(F|E)=0.5. Thus, P(E and F)=0.15
Bayes' theorem is transforming preceding probabilities into succeeding probabilities. It is based on the principle of conditional probability. Conditional probability is the possibility that an event will occur because it is dependent on another event.
P(F|E)=P(E and F)÷P(E)
It is given that P(E)=0.3,P(F|E)=0.5
Using Bayes' formula,
P(F|E)=P(E and F)÷P(E)
Rearranging the formula,
⇒P(E and F)=P(F|E)×P(E)
Substituting the given values in the formula, we get
⇒P(E and F)=0.5×0.3
⇒P(E and F)=0.15
∴The correct answer is 0.15.
If, E and F are two events and that P(E)=0.3 and P(F|E)=0.5. Thus, P(E and F)=0.15.
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I'm not sure if this dividing,multiplying,subtracting or adding but for adding i got 6 as my answer.I don't know if this the correct answer but its better than having no answer right?
I’m confused?? Do you just need 1/3 of 12? That’s 4 because 12 x 1 =12 and 12/3 is 4 lol
Answer:
A
Step-by-step explanation:
Mean:27
median:25
Mode:25
Range:11
