Tennis great Roger Federer made 63% of his first serves in a recent season. When Federer made his first serve, he won 78% of the points. When Federer missed his first serve and had to serve again, he won only 57% of the points. Suppose you randomly choose a point on which Federer served. You get distracted before seeing his first serve but look up in time to see Federer win the point. What's the probability that he missed his first serve?

Sounds like a Bayes Theorem problem.

Events:

F: Roger makes his first serve.  We'll write ~F for "not F".

P(F) = .63

P(~F) = 1 - .63 = .37

W: Roger wins the point.  We don't know P(W) but we are given

P(W | F) = .78

P(W | ~F) = .57

We're asked for

P(~F | W)

The basic conditional probability theorem is

P(~F and W) = P(~F | W) P(W) = P(W | ~F) P(~F)

P(~F | W) = ( P(W | ~F) P(~F) ) / P(W)

We write

P(W) =  P(W | F) P(F) +  P(W | ~F) P(~F)

Substituting gives Bayes' Theorem:

P(~F | W) = ( P(W | ~F) P(~F) ) / ( P(W | F) P(F) +  P(W | ~F) P(~F) )

We know all the parts so we substitute,

P(~F|W) = ( .57(.37) ) / (.78(.63) + .57(.37) ) = 0.30029901751388294

Let's call that 30%

30%

so firstly, we need to isolate the y variables to be able to solve these inequalities. firstly, add 0.5x on both sides of the first inequality and subtract 1.5x on both sides of the second inequality:

now since the slope is positive for the first inequality, this means that the line going upwards belongs to the first inequality, and the line going downwards belongs to the second inequality.

next, since y ≥ in the first inequality, this means that the shaded region will be above the first inequality's line, thus shading regions a and b.

next, since y ≤ in the second inequality, this means that the shaded region is going to be below this line, thus shading regions a and c.

since both lines shade region a, this means that region a is the solution.

step-by-step explanation:

mark brainliest!