The binomial distribution is one of the easier distributions to handle in terms of structure and calculation. Here’s what you need to know in order to choose a binomial approach in an experiment:
Rule
A random variable
Rule
The probability of getting exactly
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where
Example 1
You roll four dice and look for the number of sixes. The random variable is then
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When you roll a die, you either get a
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Now you can calculate the probability of getting either
You do that by using the formula above. Then you can put the numbers you get into a table:
| 0 | 1 | 2 | 3 | 4 |
| | | | | |
This is the probability distribution of
Note! The sum of the probabilities in a probability distribution is always
Example 2
A bus company increases how often it inspects passengers’ tickets. They assume that 1 out of 5 passengers travels without a ticket. If they inspect the tickets of 20 random passengers, what’s the probability that
1 in 5 ride without tickets, which is what you’re being asked to examine. That means that
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That makes this a binomial distribution with
The probability that exactly one of the
The probability that exactly five of the 20 ride without a ticket is around
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To calculate
Example 3
Stephen King participates in a quiz with 50 questions where every question has four alternatives. Unfortunately, Stephen has forgotten to prepare at all, forcing him to guess on every question.
The probability of guessing the correct answer to a question with four alternatives is
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becomes
Sadly, Stephen is probably never going to Paris.
The sum of these probabilities is
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If you insert this into the expression above, you get that
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It seems like Stephen at least gets to go to the Museum of Natural History for free.
If the data set of a binomial distribution becomes very large, the set follows a normal distribution rather than the binomial distribution. In that case you can use these formulas:
Rule
The binomial distribution has an expected value, variance, and standard deviation as follows:
If
A rule of thumb is that if