Google Sheets BINOMDIST Function: Syntax, Examples & Tips

What Is BINOMDIST?

BINOMDIST calculates probabilities from the binomial distribution. It applies whenever you repeat the same yes/no experiment a fixed number of times, each attempt is independent, and the chance of success is the same every time. Coin flips, email opens, defective parts in a batch, and free throws all fit this pattern.

BINOMDIST is the legacy name. The modern equivalent in Google Sheets is BINOM.DIST, which takes exactly the same four arguments and returns the same results. Either name works; BINOM.DIST is preferred in new spreadsheets.

How BINOMDIST Works

You tell the function how many trials there are, the probability of success on each, and the number of successes you care about. The cumulative argument then decides the question being answered:

• FALSE: probability of exactly that many successes (the probability mass function)
• TRUE: probability of at most that many successes (the cumulative distribution function)

Basic Examples

Exactly 3 heads in 10 coin flips

=BINOMDIST(3, 10, 0.5, FALSE)

Returns about 0.1172, an 11.7% chance.

At most 3 heads in 10 flips

=BINOMDIST(3, 10, 0.5, TRUE)

Returns about 0.1719.

At least 8 successes

=1 - BINOMDIST(7, 20, 0.3, TRUE)

The probability of 8 or more successes in 20 trials with a 30% success rate. Subtract the "7 or fewer" probability from 1.

Between two values

=BINOMDIST(12, 50, 0.2, TRUE) - BINOMDIST(7, 50, 0.2, TRUE)

The probability of between 8 and 12 successes, inclusive.

Translating Common Questions

Common Use Cases

• Quality control: chance of finding more than 2 defects in a sample of 50
• Marketing: probability that at least 30 of 200 recipients click, given a typical click rate
• Sales: chance of closing a certain number of deals from a pipeline
• Sports and games: likelihood of a set number of wins
• Capacity planning: probability that more customers show up than you have slots for

Common Errors

• #NUM!: num_successes is negative or greater than num_trials, or prob_success is outside 0 to 1.
• #VALUE!: An argument is non-numeric, or cumulative is not TRUE/FALSE.
• Off-by-one mistakes: "At least 8" needs 1 - BINOMDIST(7, …, TRUE), not 8.
• Non-independent trials: The binomial model assumes trials do not affect each other. Sampling without replacement from a small group calls for HYPGEOMDIST instead.

Tips and Best Practices

• The expected number of successes is n × p. Compare it with your result as a sanity check.
• Build a full distribution table by listing 0 to n in a column and referencing it in BINOMDIST with FALSE; chart the result to see the shape.
• For the reverse problem, finding the number of successes that matches a probability, use BINOM.INV.
• Round probabilities for reports with ROUND.

Related Functions

• BINOM.INV: smallest count whose cumulative probability meets a target
• BETADIST: models the success rate itself
• AVERAGE: the mean of a data set
• ROUND: tidy up probability results
• IF: turn a probability into a decision