Inverse Binomial Distribution in Excel
The BINOM.INV function is categorized under Statistical functions. It will calculate the inverse Binomial Distribution in Excel. That is, for a given number of independent trials, the function will return the smallest value of x (the number of successes) for a specified Cumulative Binomial Distribution probability. For example, we can use it to calculate the minimum number of tosses of a coin for which there is a 50% chance of at least 10 heads.
As a financial analyst, BINOM.INV is useful in analyzing the best stocks to invest in. We can use the function to understand how a portfolio will be affected by the addition or removal of stocks.
The BINOM.INV function was introduced in MS Excel 2010 and hence is unavailable in earlier versions.
The BINOM.INV function uses the following arguments:
- Trials (required argument) – It is the number of Bernoulli trials. That is, it is the number of independent trials that are to be done. Excel will truncate the value to an integer if we provide it in decimal.
- Probability_s (required argument) – It is the probability of success in a single trial.
- Alpha (required argument) – It is the probability of Cumulative Binomial distribution. It should be between 0 and 1.
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How to use Inverse Binomial Distribution in Excel
To understand the uses of the BINOM.INV function, let us consider a few examples:
Suppose we are given the following data:
Based on above information, we will calculate the smallest value for which the cumulative binomial distribution is greater than or equal to a criterion value. The formula to use is:
We get the result below:
So, the minimum number of trials is 3, for which the binomial cumulative distribution is 75%.
Things to remember about Inverse Binomial Distribution in Excel
- The BINOM.INV function is an updated version of the CRITBINOM function, which is available in older versions of Excel.
- #VALUE! error – Occurs when any of the arguments provided is non-numeric.
- #NUM! error – Occurs when:
- The given trial argument is less than zero.
- The probability_s argument provided is less than zero or greater than 1.
- The given alpha argument is less than zero or greater than 1.
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