Binomial Test Calculator

Understanding the Binomial Test

The Binomial Test is a statistical test used to determine whether the proportion of successes in a single trial is equal to a hypothesized value. It's particularly useful when dealing with binary outcomes (success or failure) and you want to see if the observed proportion in your sample significantly differs from a known or expected proportion.

For example, if you expect a coin to land heads 50% of the time (hypothesized proportion = 0.5) and you flip it 100 times, observing 60 heads, the binomial test can help you determine if this deviation (60% heads) is statistically significant or just due to random chance.

• Number of Successes: The count of successful outcomes in your experiment.
• Number of Trials: The total number of independent experiments or observations.
• Hypothesized Proportion: The expected proportion of successes under the null hypothesis (the value you are testing against).
• Significance Level: The threshold (alpha) used to decide if the result is statistically significant (typically 0.05). If the p-value is less than or equal to the significance level, we reject the null hypothesis.

This calculator provides the p-value, which quantifies the probability of observing a sample proportion as extreme as, or more extreme than, the one calculated from your sample, assuming the null hypothesis is true.