A Type II error occurs when

A Type II error occurs when

• A. There was an effect and you missed it.
• B. There is no effect and you conclude there is.
• C. There is an effect and you correctly detect it.
• D. There is no effect and you fail to reject it.

Answer: (A)

Type II error happens when there is a real effect but you fail to detect it. In hypothesis testing you compare the null hypothesis of “no effect” to the alternative of “an effect.” If the true state is that there is an effect, but your test does not reach statistical significance, you fail to reject the null—this is a Type II error. The option that says there was an effect and you missed it is the precise description of this situation. For reference: concluding there is an effect when there isn’t one describes a Type I error (false positive). detecting an effect when it exists and you correctly identify it is the correct outcome. and failing to reject the null when there is no effect is also a correct decision given the true state. Power, which is 1 minus the probability of a Type II error, reflects how well a test can detect real effects.

Type II error happens when there is a real effect but you fail to detect it. In hypothesis testing you compare the null hypothesis of “no effect” to the alternative of “an effect.” If the true state is that there is an effect, but your test does not reach statistical significance, you fail to reject the null—this is a Type II error. The option that says there was an effect and you missed it is the precise description of this situation.

For reference: concluding there is an effect when there isn’t one describes a Type I error (false positive). detecting an effect when it exists and you correctly identify it is the correct outcome. and failing to reject the null when there is no effect is also a correct decision given the true state. Power, which is 1 minus the probability of a Type II error, reflects how well a test can detect real effects.