Quantitative Methods Questions
A type II error in hypothesis testing refers to the situation where the null hypothesis is incorrectly accepted, despite it being false. In other words, it occurs when the researcher fails to reject the null hypothesis when it should have been rejected. This error is also known as a false negative. It implies that the researcher failed to find a significant effect or relationship between variables, even though one exists in reality. The probability of committing a type II error is denoted as β (beta) and is directly related to the power of the statistical test.