<em>Y</em>₁ and <em>Y</em>₂ are independent, so their joint density is

By definition of conditional probability,
P(<em>Y</em>₁ > <em>Y</em>₂ | <em>Y</em>₁ < 2 <em>Y</em>₂) = P((<em>Y</em>₁ > <em>Y</em>₂) and (<em>Y</em>₁ < 2 <em>Y</em>₂)) / P(<em>Y</em>₁ < 2 <em>Y</em>₂)
Use the joint density to compute the component probabilities:
• numerator:






• denominator:

(I leave the details of the second integral to you)
Then you should end up with
P(<em>Y</em>₁ > <em>Y</em>₂ | <em>Y</em>₁ < 2 <em>Y</em>₂) = (1/6) / (2/3) = 1/4
Answer:
There is a 90.32% probability that the cake was baked by Doug.
Step-by-step explanation:
We have these following probabilities:
A 70% probability that Doug bakes the cake.
A 30% probability that Jeremy bakes the cake.
A 40% probability that a cake baked by Doug gets a thumbs up.
A 10% that a cake baked by Jeremy gets a thumbs up.
One cake was selected at random on 10/01/2014 and got a "thumbs up".
1. Find the probability that the cake was baked by Doug.
The probability that a baked cake gets a thumbs up is:

Of those, 0.7*0.4 = 0.28 are baked by Doug.
So the probability is:

There is a 90.32% probability that the cake was baked by Doug.
Answer:
<h2>The answer is A 14.6</h2>
Step-by-step explanation:
the diameter is twice the length of the radius soooo 7.3x2=14.6
making the answer A
:D
Answer:
Its 2/9, sorry I can't show the explanation I have to do my work.
Step-by-step explanation: