๐ŸŽฒprobability

Binomial Probability

P(X = k) = C(n,k) ร— pแต ร— (1 - p)โฟโปแต

The binomial probability formula calculates the probability of getting exactly k successes in n independent Bernoulli trials, each with the same probability of success p. It is one of the most important discrete probability distributions in statistics.

Variables

P(X = k)=Binomial Probability

The probability of exactly k successes

n=Number of Trials

The fixed number of independent trials

k=Number of Successes

The desired number of successes (0 โ‰ค k โ‰ค n)

p=Probability of Success

The probability of success on each individual trial

Example Calculation

Scenario

A fair coin is flipped 10 times. What is the probability of getting exactly 7 heads?

Given Data

n:10
k:7
p:0.5

Calculation

P(X = 7) = C(10,7) ร— (0.5)โท ร— (0.5)ยณ = 120 ร— 0.0078125 ร— 0.125

Result

P(X = 7) = 0.1172

Interpretation

There is approximately an 11.72% chance of getting exactly 7 heads in 10 flips of a fair coin. While 7 heads is more than expected (5), it is not extremely unlikely.

When to Use This Formula

  • โœ“Calculating probabilities for a fixed number of independent yes/no trials
  • โœ“Quality control problems where items are classified as defective or not defective
  • โœ“Survey analysis where each respondent has the same probability of a particular response
  • โœ“Modeling the number of successes in repeated Bernoulli experiments

Common Mistakes

  • โœ—Forgetting to include the binomial coefficient C(n,k) which counts the number of arrangements
  • โœ—Using the binomial distribution when trials are not independent
  • โœ—Confusing P(X = k) with cumulative probabilities P(X โ‰ค k)
  • โœ—Applying the binomial model when the probability of success changes between trials

Calculate This Formula Instantly

Snap a photo of any problem and get step-by-step solutions.

Download StatsIQ

FAQs

Common questions about this formula

There must be a fixed number of trials (n), each trial must be independent, each trial must have exactly two outcomes (success or failure), and the probability of success (p) must be the same for every trial. These are sometimes called the BINS conditions.

To find P(X โ‰ค k), sum the individual probabilities P(X = 0) + P(X = 1) + ... + P(X = k). For large n, you can approximate the binomial distribution with the normal distribution using ฮผ = np and ฯƒ = โˆš(np(1-p)), applying a continuity correction.

More Formulas