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Lynna [10]
3 years ago
9

A red die, a blue die, and a yellow die (all six sided) are rolled. we are interested in the probability that the number appeari

ng on the blue die is less than that appearing on the yellow die, which is less than that appearing on the red die. that is, with b, y, and r denoting, respectively, the number appearing on the blue, yellow, and red die, we are interested in p(b < y < r).
Mathematics
1 answer:
NISA [10]3 years ago
6 0

5/54 or approximately 0.092592593  
There are 6^3 = 216 possible outcomes of rolling these 3 dice. Let's count the number of possible rolls that meet the criteria b < y < r, manually.
 r = 1 or 2 is obviously impossible. So let's look at r = 3 through 6.
 r = 3, y = 2, b = 1 is the only possibility for r=3. So n = 1
 r = 4, y = 3, b = {1,2}, so n = 1 + 2 = 3
 r = 4, y = 2, b = 1, so n = 3 + 1 = 4
 r = 5, y = 4, b = {1,2,3}, so n = 4 + 3 = 7
 r = 5, y = 3, b = {1,2}, so n = 7 + 2 = 9
 r = 5, y = 2, b = 1, so n = 9 + 1 = 10
 
 And I see a pattern, for the most restrictive r, there is 1 possibility. For the next most restrictive, there's 2+1 = 3 possibilities. Then the next one is 3+2+1
= 6 possibilities. So for r = 6, there should be 4+3+2+1 = 10 possibilities.
Let's see
 r = 6, y = 5, b = {4,3,2,1}, so n = 10 + 4 = 14
 r = 6, y = 4, b = {3,2,1}, so n = 14 + 3 = 17
 r = 6, y = 3, b = {2,1}, so n = 17 + 2 = 19
 r = 6, y = 2, b = 1, so n = 19 + 1 = 20 
 And the pattern holds. So there are 20 possible rolls that meet the desired criteria out of 216 possible rolls. So 20/216 = 5/54.
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Answer:

See steps below

Step-by-step explanation:

Let X be the random variable that measures the lifespan of a bulb.

If the random variable X is exponentially distributed and X has an average value of 24 month, then its probability density function is

\bf f(x)=\frac{1}{24}e^{-x/24}\;(x\geq 0)

and its cumulative distribution function (CDF) is

\bf P(X\leq t)=\int_{0}^{t} f(x)dx=1-e^{-t/24}

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The probability that the bulb fails the first year is

\bf P(X\leq 12)=1-e^{-12/24}=1-e^{-0.5}=0.39347

• If the bulb is in good condition at the end of 18 months, what is the probability that the bulb will be in good condition at the end of 24 months?

Let A and B be the events,

A = “The bulb will last at least 24 months”

B = “The bulb will last at least 18 months”

We want to find P(A | B).

By definition P(A | B) = P(A∩B)P(B)

but B⊂A, so  A∩B = B and  

\bf P(A | B) = P(B)P(B) = (P(B))^2

We have  

\bf P(B)=P(X>18)=1-P(X\leq 18)=1-(1-e^{-18/24})=e^{-3/4}=0.47237

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\bf P(A | B)=(P(B))^2=(0.47237)^2=0.22313

• If the signal has six red bulbs, what is the probability that at least one of them needs replacement at the first inspection? Assume distribution of lifetime of each bulb is independent

If the distribution of lifetime of each bulb is independent, then we have here a binomial distribution of six trials with probability of “success” (one bulb needs replacement at the first inspection) p = 0.39347

Now the probability that exactly k bulbs need replacement is

\bf \binom{6}{k}(0.39347)^k(1-0.39347)^{6-k}

<em>Probability that at least one of them needs replacement at the first inspection = 1- probability that none of them needs replacement at the first inspection. </em>

This means that,

<em>Probability that at least one of them needs replacement at the first inspection =  </em>

\bf 1-\binom{6}{0}(0.39347)^0(1-0.39347)^{6}=1-(0.60653)^6=0.95021

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