Binomial Distribution Practice: Part A Solution & Part B Explanation

In summary, the conversation discusses a problem involving breaking eggs, with the goal of finding the probability of breaking a certain number of eggs in each case. The solution involves setting up probabilities for each type of egg and using multiplication and addition to find the overall probability.
  • #1
planauts
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Homework Statement



http://puu.sh/dOcM
Answer:
http://puu.sh/dOcZ

Homework Equations



The Attempt at a Solution


I got Part A.
For part A, this is what I did:

I did Egg A: X ~ (6,(1/6)) P(X = 1) and did something similar for Egg B. I then multiplied both to get the answer for Part A.
http://puu.sh/dOfV

For Part B, I'm a bit confused. I tried doing cases. As in:
(broken eggs): AA , BB , AB (same as BA)
Then I did:
AA: X ~ (6,(1/6)) P(X = 2)
BB: Y ~ (6,(1/10)) P(X = 2)
AB: X ~ (6,(1/6)) P(X = 2) * Y ~ (6,(1/10)) P(X = 2)

My work:
http://puu.sh/dOh8


And then, I tried multiplying and adding the three values. But I didn't get the correct answer.

Could someone help me out please? Thanks
 
Last edited by a moderator:
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  • #2
If two type A are broken then we must have 0 type B broken in order to have two broken altogether.

RGV
 
  • #3
Wow, thanks. I tried it out. It works :) thanks.
 

1. What is a binomial distribution?

A binomial distribution is a probability distribution that describes the possible outcomes of a given experiment with two possible outcomes (success or failure) and a fixed number of trials. It is often used to model situations where there are only two possible outcomes and the trials are independent.

2. What is the formula for calculating the probability of a specific number of successes in a binomial distribution?

The formula for calculating the probability of x successes in n trials in a binomial distribution is P(x) = (n choose x) * p^x * (1-p)^(n-x), where n is the number of trials, p is the probability of success, and x is the number of successes.

3. What is the difference between Part A and Part B in the "Binomial Distribution Practice"?

Part A of the "Binomial Distribution Practice" involves solving a specific problem using the binomial distribution formula, while Part B asks for an explanation of the solution and the steps taken to solve the problem.

4. How is the binomial distribution different from the normal distribution?

The binomial distribution is a discrete distribution, meaning that it deals with a finite number of possible outcomes. On the other hand, the normal distribution is a continuous distribution, meaning that it deals with an infinite number of possible outcomes. Additionally, the shape of the two distributions is different, with the binomial distribution being more skewed towards one end.

5. What real-world situations can be modeled using the binomial distribution?

The binomial distribution can be used to model a variety of real-world situations, such as coin flipping, election results, and the success rate of medical treatments. It is also commonly used in quality control and market research.

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