Rejection of a true null hypothesis is known as which error?

• A. Type I error
• B. Type II error
• C. Sampling error
• D. Measurement error

Answer: (A)

Rejecting a true null hypothesis is a Type I error. In hypothesis testing, the null usually posits no effect or no difference. If your sample leads you to conclude there is an effect when, in the population, there actually isn’t, you’ve made a false positive. The chance of this happening is set by the significance level, alpha, typically 0.05. By contrast, a Type II error occurs when you fail to reject a false null—that is, you miss a real effect. The other terms describe different sources of error: sampling error comes from using a sample instead of the whole population, and measurement error arises from imperfections in the measurement process.