Type I and II Errors
Type I error is falsely rejecting a true null hypothesis (false positive); Type II error is failing to reject a false null hypothesis (false negative).
Formula
α = P(reject H₀ | H₀ true); β = P(fail to reject H₀ | H₀ false)
Real World
The UK's pesticide approval body (HSE) sets a stringent significance threshold to minimise Type I errors — falsely approving a harmful pesticide is considered far more dangerous than the Type II error of blocking a safe one.
Exam Focus
In exam scenarios, identify which error type has worse consequences and justify the appropriate significance level — this shows application beyond definition recall.
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