Type 2 Error occurs when an experiment or analysis incorrectly concludes that the independent variable has no effect on the dependent variable, when in reality, the independent variable does have an effect. This is also known as a “false negative.”
Example
A researcher tests a new reading intervention to see if it improves students’ reading skills. The results show no significant improvement, so the researcher concludes that the intervention had no effect. However, the intervention actually did improve reading skills, but the study failed to detect it due to factors like a small sample size or poor measurement. This is a Type 2 Error because the effect of the independent variable was missed.