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The difference between type I and type II errors

Subject: Statistics
Courses: K300, K310, S301
Posted by: Damon

Statistics is all about trying to make generalizations based on something we can actually see and measure - running an experiment, taking a survey, or considering evidence in a courtroom.

Any time we do this, there is a chance of drawing the wrong conclusion - what we commonly call false positives and false negatives.

In stats classes like K300 and S301, these errors are called by the more confusing names "Type I" and "Type II" errors. In this video Damon gives us an easy way to remember which is which, and why it's important for your exam!