The interpretation of a test of significance can depend on the sample size and the practical context of the test. Write a short explanation of how sample size can affect the decision about statistical significance and whether or not the result is of any practical significance.
3 answers
https://www.google.com/search?client=safari&rls=en&q=practical+statistical+significance&ie=UTF-8&oe=UTF-8&gws_rd=ssl
So can you confirm if this is good enough? (4marks)
Sample size is a very important factor in terms of the test of significance. Increasing the sample size increases the power of a significance test. Here the 'power' of a significance test measures its ability to detect an alternative hypothesis.
Sample size is a very important factor in terms of the test of significance. Increasing the sample size increases the power of a significance test. Here the 'power' of a significance test measures its ability to detect an alternative hypothesis.
However, if you need sample of thousands to get statistical significance, it probably is not of practical significance in individual cases.
2 answers