1.28x.06=1.68+28=(29.68)
2.28x.2=5.6+28=(33.6)
they would take their total bill (28 bucks) times .2 to get 20%
F(-2)+g(5) = 3(-2) -1 + (-5) + 6
f(-2)+g(5) = -6 -1 - 5 + 6
f(-2)+g(5) = -6
Answer:2.088
Step-by-step explanation:
2.088
Answer:
202.3 ounces of real silver
Step-by-step explanation:
Another example would be like pizza. If there are 6 slices of pizza in each box, then 2 boxes of pizza would have 6 + 6 slices = 12 slices. It is 6 slices each * 2 boxes = 12 slices total. The same applies to the coin situation, for every additional coin, multiply 0.85 by the number of coins to get the total weight of real silver.
If there are 238 silver coins, then you have 238 0.85 ounces of real silver. Multiplying 238 by 0.85 to simplify gives you 202.3 ounces of real silver.
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%
Answer: 30%