Question

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.

Answer 1

https://www.google.com/search?client=safari&rls=en&q=practical+statistical+significance&ie=UTF-8&oe=UTF-8&gws_rd=ssl

Answer 2

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.

Answer 3

However, if you need sample of thousands to get statistical significance, it probably is not of practical significance in individual cases.