The BINOMDIST function is used to calculate the binomial distribution. This is useful in situations where there is a fixed number of trials, the trials are independent of each other, the outcome of each trial is either success or failure, and the probability of success or failure is constant throughout the test.
The arguments of the function represent the following:
number |
the number of occurrences of success in the trials |
trials |
the number of trials to be performed |
probability |
the probability of success for a single trial |
cumulative |
a logical value, which determines the form of the function: TRUE calculates the cumulative distribution function, which gives the probability that there are at most number successes FALSE calculates the probability mass function, which gives the probability that there are exactly number successes |
For example, we want to know the probability of getting 12 heads from 20 flips of a coin. Each flip of the coin can only give either heads or tails ("success" or "failure"), and the probability of heads on each flip is constant at 0.5. Therefore, setting cumulative to FALSE, the formula:
BINOMDIST(12, 20, 0.5, FALSE)
returns the probability 0.12 that we will get exactly 12 successes from 20 trials.
If cumulative is set to TRUE, then the formula:
BINOMDIST(12, 20, 0.5, TRUE)
returns 0.87, that is the probability that we will get at most 12 heads (12 or less).
See also: