2. Here are the historical probabilities p(x) = P(X=x) that a fixed length of cast-iron piping will be manufactured and be found, on inspection, to have various numbers X of potentially weakening defects: p(x) F(x) 0 .45 1 .21 2 .13 3 .12 4 .09 a) Create a table of the cumulative distribution function F(x) = P(X≤x) for this random variable. Use the function F(x) to find the probability will have some defects but no more than 3 defects. b) Calculate the expected number of defects in a pipe E(X).

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Chapter1: Combinatorial Analysis
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2. Here are the historical probabilities p(x) = P(X=x) that a fixed length of cast-iron piping
will be manufactured and be found, on inspection, to have various numbers X of potentially
weakening defects:
p(x)
F(x)
0
.45
1
.21
2
.13
3
.12
4
.09
a) Create a table of the cumulative distribution function F(x) = P(X≤x) for this random
variable. Use the function F(x) to find the probability will have some defects but no more than 3
defects.
b) Calculate the expected number of defects in a pipe E(X).
Transcribed Image Text:2. Here are the historical probabilities p(x) = P(X=x) that a fixed length of cast-iron piping will be manufactured and be found, on inspection, to have various numbers X of potentially weakening defects: p(x) F(x) 0 .45 1 .21 2 .13 3 .12 4 .09 a) Create a table of the cumulative distribution function F(x) = P(X≤x) for this random variable. Use the function F(x) to find the probability will have some defects but no more than 3 defects. b) Calculate the expected number of defects in a pipe E(X).
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