Type I Error - Rejecting the null hypothesis eventhough it is true
Type II error, also known as a "false negative": the error of not rejecting a null hypothesis when the alternative hypothesis is the true state of nature
I liked below comment from Khan Academy
The easiest way to think about Type 1 and Type 2 errors is in relation to medical tests. A type 1 error is where the person doesn't have the disease, but the test says they do (false positive). A type 2 error is where the person has the disease but the test doesn't pick it up (false negative).
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