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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Answer: The .30 per mile is the independent, because it is manipulated, and changed throughout. DRY MIX : Dependent, Responding, Y axis. Manipulated, Independent, X axis.
C - (x-3)^2=36
If we expand (x-3)^2=36:
(x-3)(x-3)=36
x^2-3x-3x+9=36
x^2-6x+9=36
Then subtract 36
x^2-6x-27=0
Any second part or anything else to look at?
It's the first one. y = 3x
proportional means they are just some multiple of the other.
