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Statistics vocabulary · Hypothesis Testing

Significance level

Meaning in statistics, with examples

nounCore term

In statistics, significance level means: The threshold, chosen before a test, below which a p-value is treated as statistically significant; it is also the accepted risk of a Type I error.

In Turkish: anlamlılık düzeyi, alfa düzeyi

How it is used

Written α (alpha) and most often set at 0.05, sometimes at 0.01 or 0.10. Typical phrases are 'at the 5% significance level' and 'significant at α = .05'. Lowering alpha reduces false positives but also reduces power.

Example sentences

  1. All tests used a significance level of 0.05.

  2. The effect is significant at the 5% level but not at the 1% level.

Common collocations

  • set the significance level
  • at the 5% significance level
  • alpha level
  • a significance level of 0.01
  • p-valueThe probability of getting a result at least as extreme as the one observed if the null hypothesis were true; a small value means the data would be surprising under the null.
  • type I errorRejecting a null hypothesis that is actually true, in other words concluding that an effect exists when it does not; a false positive.
  • statistical significanceThe conclusion that a result is unlikely to be due to chance alone, judged by comparing the p-value with a chosen significance level such as 0.05.
  • statistical powerThe probability that a test will detect an effect when a real effect of a given size exists; it equals one minus the probability of a Type II error.

More terms: Hypothesis Testing

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