Easily determine the risk of making a Type 1 Error (Alpha Error) in your statistical tests. Our calculator helps you compare your p-value against the chosen significance level to understand potential false positives in hypothesis testing. Make informed decisions quickly and confidently.
Formula:
The Type 1 Error (alpha, α) is the probability of rejecting a true null hypothesis (H0) when it is actually true. When evaluating a hypothesis test, we compare the calculated p-value to the pre-determined significance level (α) to make a decision:
- If p-value ≤ α: Reject H0. There is a risk of making a Type 1 Error.
- If p-value > α: Fail to Reject H0. No Type 1 Error is made in this instance based on the decision.
Where:
- α (Alpha): The significance level, typically a chosen value like 0.05 or 0.01. It represents the maximum acceptable probability of committing a Type 1 Error.
- p-value: The probability of observing a test statistic as extreme as, or more extreme than, the one observed, assuming the null hypothesis is true.