Binomial Parameters
REAL-TIME
20
The total number of independent trials
0.50
Probability of success on each trial (0 to 1)
10
Exact number of successes to calculate
Select the type of probability to calculate
15
Upper bound for between calculation
Probability Results
Selected Probability
0.1762
P(X = 10) = 0.1762
Cumulative Probability
0.5881
P(X ≤ 10) = 0.5881
Mean (Expected Value)
10.00
μ = n × p
Variance
5.00
σ² = n × p × (1-p)
Probability Summary
| Number of Successes (k) | Probability P(X = k) | Cumulative P(X ≤ k) | Percentage |
|---|
Probability Distribution
Most Likely: 10 successes
Probability: 17.6%
Key Statistics
- Standard Deviation: 2.24
- Mode: 10
- Skewness: 0.00
- Kurtosis: -0.10
- Range (95% CI): 6 to 14
Quick Actions
How to Use the Binomial Distribution Calculator
The binomial distribution is a fundamental probability model used to calculate the likelihood of obtaining a fixed number of successes in a specific number of independent trials. Our real-time calculator makes these complex statistical calculations simple and intuitive.
Step-by-Step Guide:
- Set the Number of Trials (n): This is the total number of independent experiments or trials you're conducting. Use the slider or directly input a value between 1 and 100.
- Define Success Probability (p): Enter the probability of success on each individual trial. This must be between 0 (impossible) and 1 (certain).
- Specify Success Count (k): Determine the exact number of successes you want to calculate the probability for.
- Choose Calculation Type: Select whether you want the probability of exactly k successes, at most k successes, at least k successes, or between two values.
- View Results: The calculator instantly displays probabilities, key statistics, and visualizes the distribution.
Real-World Applications:
- Quality Control: Determine the probability of a certain number of defective items in a production batch.
- Medical Testing: Calculate the likelihood of a specific number of positive results in clinical trials.
- Survey Analysis: Estimate probabilities in opinion polls and survey responses.
- Risk Assessment: Evaluate probabilities in finance, insurance, and project management.
- Game Theory: Calculate odds in games of chance and strategic decision-making.
Binomial Formula
The binomial probability formula is:
P(X = k) = C(n,k) × p^k × (1-p)^(n-k)
Where:
- C(n,k) = binomial coefficient
- n = number of trials
- k = number of successes
- p = probability of success
Tool Features
- Real-time probability calculations
- Interactive distribution chart
- Multiple calculation types
- Detailed statistics and metrics
- Probability table with all values
- Export functionality
- Example scenarios
- Responsive design
- Save and load scenarios
- SEO optimized content