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Statistical vs Practical Significance

The practical problem with hypothesis tests is that if the sample is sufficiently large the alternative hypothesis will be accepted, no matter how small the deviation from the null hypothesis condition.

In practice we are only interested in identifying departures from the null hypothesis condition that are meaningful to the purpose of the test.

We can achieve the appropriate practical significance by adjusting the power of the test. This will usually be achieved by selecting a sample size that is neither too large or too small.

 Hypothesis testing is covered in the MiC Quality Advanced Statistics Course. Try out our courses by taking the first module of the Primer in Statistics free of charge.
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