Type I and type II errors
Topic: Management
The two kinds of error in hypothesis testing. A type I error (alpha) is rejecting a true null hypothesis: concluding there is an effect when there is none (a false positive). A type II error (beta) is failing to reject a false null hypothesis: missing a real effect (a false negative). Statistical power is the probability of detecting a real effect and rises with sample size; a power analysis before the study estimates the sample needed.
- Also known as:
- Alpha error, Beta error, Statistical power
- In Turkish:
- Tip I ve tip II hata
What does Type I and type II errors mean?
Type I and type II errors is part of the Management topic in nursing. Students meet it in class, on clinical placements and while preparing for exams.
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