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vfiekz [6]
3 years ago
15

Log base 2 of (15b- 15) - log base 2 ( - b^2 + 1 ) = 1

Mathematics
1 answer:
olga2289 [7]3 years ago
4 0
log_{2}(15b - 15) - log_{2}(-b^{2} + 1) = 1
log_{2}(\frac{15b - 15}{-b^{2} + 1}) = 1
log_{2}(\frac{15(b) - 15(1)}{-1({b^{2}) - 1(-1)}}) = 1
log_{2}(\frac{15(b - 1)}{-1(b^{2} - 1)}) = 1
log_{2}(-\frac{15(b - 1)}{b^{2} - 1}) = 1
log_{2}(-\frac{15(b - 1)}{b^{2} + b - b - 1}) = 1
log_{2}(-\frac{15(b - 1)}{b(b) + b(1) - 1(b) - 1(1)}) = 1
log_{2}(-\frac{15(b - 1)}{b(b + 1) - 1(b + 1)}) = 1
log_{2}(-\frac{15(b - 1)}{(b - 1)(b + 1)}) = 1
log_{2}(-\frac{15}{b + 1}) = 1
2^{1} = -\frac{15}{b + 1}
2 = -\frac{15}{b + 1}
2(b + 1) = (b + 1)(-\frac{15}{b + 1})
2(b) + 2(1) = -15
2b + 2 = -15
2b = 13
\frac{2b}{2} = \frac{-17}{2}
b = -8.5

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Samples of 20 parts from a metal punching process are selected every hour. Typically, 1% of the parts require rework. Let X deno
Roman55 [17]

Answer:

a) P(X>np+3\sqrt{np(1-p)}=0.017

b) P(x>1)=0.190

c) P(Y>1)=0.651

Step-by-step explanation:

This a binomial experiment where success is denoted by parts that need rework.

X ∼ B(n, p); n = 20; p = 0.01

The expected value of X is: E(X) = np =20×0.01= 0.2

The variance is: Var(X) = np(1 − p) = 0.2 × 0.99 = 0.198,

The standard deviation SD(X)= \sqrt{0.198} ≈ 0.445

a) P(X>np+3\sqrt{np(1-p)}=P(X>0.2+3×0.445)=P(X>1.535)=P(X≥2)

Probability function is given by:

\frac{n!}{x!(n-x)!} *p^x*(1-p)^{(n-x)}

P(X≥2)=1-P(X<2)=1-P(X=1)-P(X=0)= 1 - \frac{20!}{1!(20-1)!} *(0.01)^{1}*(1-0.01)^{(20-1)}-\frac{20!}{0!(20-0)!} *(0.01)^{0}*(1-0.01)^{(20-0)}

P(X≥2)=1-0.165-0.818=0.017

b) p=0.04

P(x>1)=P(x≥2)= 1 - P(x=1) - P(x=0)= 1 - \frac{20!}{0!(20-1)!} *(0.04)^{1}*(1-0.04)^{(20-1)} - \frac{20!}{0!(20-0)!} *(0.04)^{0}*(1-0.04)^{(20-0)}

P(x>1)= 1 - 0.368 - 0.442=0.190

c) In this case we consider p=0.19 (Probability that X exceeds 1)

In this experiment Y is the number of hours and n= 5 hours.

Then, we check the probability in each hour:

P(Y>1)=1- P(Y=0)

P(Y=0)=\frac{5!}{0!(5-0)!} *(0.19)^{0}*(1-0.19)^{(5-0)}=0.349

P(Y>1)=1-0.349=0.651

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