Type Two Error Calculator Single Proportion

Type II error, also known as a false negative, occurs when a test fails to reject a false null hypothesis. In the context of a single proportion, understanding and calculating type II error is crucial for making informed decisions based on statistical tests.

1. Enter the significance level (α), power, and sample size (n) in the respective fields.
2. Click the ‘Calculate’ button to see the results and chart below.

The formula for calculating the type II error probability (β) for a single proportion is:

Comparison of Type I and Type II Errors

Error Type	False Positive	False Negative
Type I	Yes	No
Type II	No	Yes

• Always ensure your sample size is large enough to detect a meaningful effect.
• Consider the consequences of both type I and type II errors when designing your study.

What is the difference between Type I and Type II errors?

Type I error is a false positive, while Type II error is a false negative. In other words, Type I error occurs when you reject a true null hypothesis, and Type II error occurs when you fail to reject a false null hypothesis.

Learn more about Type II Error

Read about the importance of power and sample size