Statistics › Section I · Hypothesis testing with one sample › Topic I.2
Type I and Type II errors
No test can guarantee a correct verdict. Knowing the two ways a test can go wrong, and what each costs, is how studies choose their significance level and their sample size.
In this topic
- Two ways to be wrong
- The four outcomes
- Type I: the false alarm
- Type II: the missed detection
- The seesaw
- Worked example: which error should each device fear?
- Power: the detection rate
- Worked example: the four cells of a drug trial
- Common mistakes to avoid
- Key takeaways
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