Type II Error
The failure to reject a false null hypothesis (a false negative).
What is Type II Error?
A Type II error occurs when a researcher concludes that there is no statistically significant effect when, in reality, a true effect exists. It is the error of missing a real discovery.
Why Type II Error Matters
Type II errors mean missed opportunities, such as failing to approve a life-saving drug because the clinical trial didn't detect its effectiveness.
How to Interpret
The probability of making a Type II error is denoted by beta (ฮฒ). Statistical power (1 - ฮฒ) is the probability of correctly rejecting a false null hypothesis.
Example
A study evaluates a new reading intervention but uses too few students. The intervention actually works, but because the sample size was too small, the p-value is 0.15, and the researcher incorrectly concludes the intervention is ineffective.
Common Mistakes
- Assuming that a non-significant result (p > 0.05) proves the null hypothesis is true, rather than acknowledging it might be a Type II error due to low power.