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Data Science & Analytics vocabulary · A/B Testing and Experimentation

Statistical power

Meaning in data science & analytics, with examples

nounAdvanced term

In data science & analytics, statistical power means: The probability that a test will detect an effect of a given size if that effect really exists; tests are commonly designed to have 80% power.

In Turkish: istatistiksel güç, testin gücü

How it is used

Mostly used when planning experiments: power depends on sample size, effect size and the significance level. A test with low power, called 'underpowered', can easily miss real effects. Closely linked to the minimum detectable effect (MDE).

Example sentences

  1. With only two weeks of traffic, the test has very low statistical power.

  2. We did a statistical power calculation and need about 30,000 users per group.

Common collocations

  • power analysis
  • statistical power calculation
  • underpowered test
  • 80% power
  • sample sizeThe number of observations, people or units included in a sample or an experiment; larger samples usually give more reliable estimates.
  • A/B testAn experiment in which users are randomly split into two groups that see different versions of something, so you can measure which version performs better.
  • statistical significanceA sign that a result is unlikely to be explained by random chance alone, usually judged by whether the p-value falls below a threshold chosen in advance, such as 0.05.
  • p-valueThe probability of seeing a result at least as extreme as the one observed if there were really no effect, that is, if the null hypothesis were true.

This word in other fields

The same English word can have a different meaning in another field:

More terms: A/B Testing and Experimentation

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