Engineering Statistics: Binomial Distribution

In summary: This makes sense, because as k gets larger and larger, the number of available digits (0,1,2) gets smaller and smaller, making it less likely for none of them to appear. In summary, the probability of a k-digit number containing at least one 0, one 1, and one 2 is (7/9)^1 * (7/10)^{k-1} where k >= 3 is an integer.
  • #1
aeroguy77
12
0

Homework Statement



Let k >= 3 be any integer. What is the probability that a random k-digit number will have at least one 0, one 1 and one 2? (as usual every number starts with either 1,2,...9 and NOT zero)

Homework Equations



b(x : n,p) = (n x)p^x*(1-p)^(n-x) where x = 0, 1, 2, ... ,n
0 otherwise

This equation represents a binomial probability distribution. The outcome is either a success or a failure. In this case, a success would be a number containing at least a 0, 1 or 2. A failure would be otherwise.

The Attempt at a Solution



I'm not sure how to apply this equation in this situation, especially with the constraint put on k. I know that the number of "trials" must be 1. I also know that the outcome is either a success or a failure. I'm assuming that I'm looking for p in the above equation, which is the probability of success. Perhaps I'm missing something? I'm not sure, I've been attempting this for a while now with no luck.

Any advice to point me in the right direction would be great. Thanks
 
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  • #2
First of all, I don't like "at least" questions, I prefer them formulated as "at most". So you could use the complement rule to reformulate the question to "What is the probability that the chosen integer will contain no 0, 1 or 2".

Hint: consider the first digit and the remaining (k - 1) digits separately. Then build the k-digit number by randomly choosing from the set {1, 2, ..., 9} for the first digit and {0, 1, ..., 9} for the second one. Look at the event "a chosen numebr is not 0, 1 or 2".
 
  • #3
First of all, thanks CompuChip, I'm getting closer at an answer.
This is what I've come up with so far:

P(1st digit not being 1 or 2) = 7/9
P(2nd digit not being 0,1 or 2) = 7/10
P(3rd '' '' '' '' ) = 7/10
.
.
.
P(Kth " " " " ) = 7/10

In this set, at MOST 2/k digits can be 0,1, or 2

I'm not sure how to formulate this however. My intuition tells me that eventually (at infinity) the probability of NOT having 0, 1 and 2 is zero. I'm having a real hard time grasping this.
 
  • #4
aeroguy77 said:
First of all, thanks CompuChip, I'm getting closer at an answer.
This is what I've come up with so far:

P(1st digit not being 1 or 2) = 7/9
P(2nd digit not being 0,1 or 2) = 7/10
P(3rd '' '' '' '' ) = 7/10
.
.
.
P(Kth " " " " ) = 7/10

Looks very good.
Now, what is the probability that all of these events happen at the same time.
That is, that if you choose a k-digit number, that none of the digits will be (0), 1 or 2.

Your intuition is correct by the way, if you take the probability you are about to calculate and take the limit as k goes to infinity, the probability goes to 0.
 

Related to Engineering Statistics: Binomial Distribution

What is the binomial distribution in engineering statistics?

The binomial distribution is a probability distribution that is commonly used in engineering statistics to model the number of successes in a series of independent trials, where each trial has a binary outcome (success or failure) and the probability of success remains constant throughout the trials.

How is the binomial distribution calculated?

The binomial distribution is calculated using the formula P(x) = nCx * p^x * q^(n-x), where n is the number of trials, x is the number of successes, p is the probability of success, and q = 1-p is the probability of failure.

What are some real-world applications of the binomial distribution in engineering?

The binomial distribution is commonly used in engineering to model the reliability of systems, such as electronic components or mechanical parts. It can also be used to analyze the success rate of a manufacturing process or to estimate the probability of a certain number of defects in a production run.

What is the relationship between the binomial distribution and the normal distribution?

The binomial distribution can be approximated by the normal distribution when the number of trials is large and the probability of success is not too close to 0 or 1. This is known as the central limit theorem and is frequently used in engineering statistics to simplify calculations.

How is the binomial distribution used to make predictions?

In engineering, the binomial distribution can be used to make predictions about the likelihood of a certain number of successes or failures in a series of trials. This information can be used to inform decision-making and improve processes or systems.

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