An earlier post tried to clarify Type 1 and Type II errors. However, more clarification may be needed.
Another way of thinking about Type I and Type II errors is to look at the experimenter’s conclusions.
TYPE I ERROR
If the experimenter concludes that there was a significant difference between the groups in her sample, she can only be making a Type I error or a correct decision. That is, she either found the effect (correct decision) or she thinks she found an effect that actually wasn’t there (Type I error).
An example would be a positive result on a HIV test. This person can either have HIV or have a false positive (Type 1 error).
TYPE II ERROR
If the experimenter concludes that no effect was found, she can only be making the correct decision or failing to find that effect. That is, she can either be correct in saying that there is no effect or be missing an opportunity to find that effect.
An example would be a negative result on a HIV test. This person could actually not have HIV (a correct decision) or be missing a chance to detect the disease (Type II error).
A Type II error is a lost opportunity to correctly reject the null hypothesis.