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For an experiment to be classified as a binomial distrbution four critiria have to be met:
- There must be a fixed number of trials which is denoted by n.
- Each trial only has two possible outcomes. One is labeled success and the other is failure.
- the probably of success is p. The probably of failure is 1-p
- Finally, the trials must be independent of one other (the outcome of one trial does not affect the outcomes of any other trial.)
An example of a binomial experiement is flipping a coin.
- You can set a fixed number of trials. In this case, flipping a coin 3 times.
- You label head as success and tails as failure.
- The probability of heads is p=0.5; the probability of tails is 1-p = 1-0.5 = 0.5.
- Getting heads on the first flip, doesn't change the probability of flipping heads again on the second. Thus the trials are independent.
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What is the relationship between the binomial expansion and binomial distribution?
First i will explain the binomial expansion
Why is it necessary to use a continuity correction when using a normal distribution to approximate a binomial distribution?
It is necessary to use a continuity correction when using a normal distribution to approximate a binomial distribution because the normal distribution contains real observations, while the binomial distribution contains integer observations.
Why is binomial distribution important?
Binomial distribution is the basis for the binomial test of statistical significance. It is frequently used to model the number of successes in a sequence of yes or no experiments.
What is the difference between poisson and binomial distribution?
Poisson and Binomial both the distribution are used for defining discrete events.You can tell that Poisson distribution is a subset of Binomial distribution. Binomial is the most preliminary distribution to encounter probability and statistical problems. On the other hand when any event occurs with a fixed time interval and having a fixed average rate then it is Poisson distribution.
The mean of a binomial probability distribution can be determined by multiplying?
The mean of a binomial probability distribution can be determined by multiplying the sample size times the probability of success.
