β Beta Level
power of a test = (1-β)
- Power relates to how likely a test is to distinguish an actual effect from one you could expect to happen by chance alone.
- Beta plus the power of a test is always equal to 1
- Usually, researchers will refer to
- the power of a test (e.g. a power of 0.8)
- leaving the beta level (0.2 in this case) as implied
Lower Beta?
- In theory, the lower beta, the better.
- You could simply increase the power of a test to lower the beta level.
- However, there’s an important trade-off.
- Alpha and beta levels are connected: you can’t lower one without raising the level of the other.
- For example, a Bonferroni correction
- reduces the alpha level (i.e. the probability of making a type I error)
- but inflates the beta level (the probability of making a type II error).
- False positives are minimized, but with the payoff that the possibility of false negatives are increased.
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- alpha level: usually just called alpha(α)
- the probability of a type I error
- rejecting the null hypothesis when it is true.
- beta level: usually just called beta(β)
- the probability of a type II error
- accepting the null hypothesis when it’s false.
- the incorrect conclusion that there is no statistical significance (if there was, you would have rejected the null).
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