Macie's question at Yahoo Answers regarding binomial probability

In summary, the probability of getting 10 or fewer "sixes" when throwing a die 60 times is approximately 0.5834. This was calculated using the binomial probability formula and summing up the probabilities for each possible number of "sixes" from 0 to 10.
  • #1
MarkFL
Gold Member
MHB
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Here is the question:

A die is thrown 60 times. What is the probability of 10 or fewer "sixes" ?

I have posted a link there to this topic so the OP can see my work.
 
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  • #2
Hello Macie,

We want to use the binomial probability formula:

\(\displaystyle P(x)={n \choose x}p^x(1-p)^{n-x}\)

where:

\(\displaystyle 0\le x\le10\in\mathbb{Z}\)

\(\displaystyle n=60\) is the number of trials

\(\displaystyle p=\frac{1}{6}\) is the probability of rolling a six in any trial.

We want to find the probability that we get zero 6's or 1 6 or 2 6's or...10 6's. So we want to sum up the probabilities for $x=0$ to $x=10$. With the aid of technology, we find:

\(\displaystyle P(X)=\sum_{x=0}^{10}\left({60 \choose x}\left(\frac{1}{6} \right)^x\left(\frac{5}{6} \right)^{60-x} \right)=\frac{9504082209854658458425546996295452117919921875}{16291225993563085829774250757924867955220283392}\)

\(\displaystyle P(X)\approx0.583386555045634235343489438735516181052152146974030836906911\)

I entered the command:

sum of nCr(60,k)(1/6)^k(5/6)^(60-k) for k=0 to 10

at Wolfram|Alpha: Computational Knowledge Engine
 

FAQ: Macie's question at Yahoo Answers regarding binomial probability

1) What is binomial probability?

Binomial probability is a mathematical concept that calculates the likelihood of a specific number of successes in a series of independent trials. It is typically used in situations where there are only two possible outcomes, such as heads or tails in a coin flip.

2) How is binomial probability calculated?

Binomial probability is calculated using the formula P(x) = nCx * p^x * (1-p)^(n-x), where n is the total number of trials, x is the number of successes, and p is the probability of success in each individual trial. This formula represents the probability of getting exactly x successes in n trials.

3) Can binomial probability be used in real-life situations?

Yes, binomial probability is commonly used in real-life situations, such as in quality control or market research. For example, a company may use binomial probability to determine the likelihood of a product passing quality standards or a researcher may use it to calculate the probability of a certain response in a survey.

4) What are the assumptions of binomial probability?

The assumptions of binomial probability are that there are only two possible outcomes, the trials are independent of each other, and the probability of success remains constant throughout all trials. These assumptions must be met in order for the binomial probability formula to be accurate.

5) How is binomial probability different from other probability distributions?

Binomial probability is a specific type of discrete probability distribution that is used for situations with only two possible outcomes. Other probability distributions, such as the normal distribution or Poisson distribution, may be used for different types of data or outcomes. Additionally, binomial probability only considers a fixed number of trials, whereas other distributions may allow for a varying number of trials.

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