What to do when sample size is too small during usability study?

1. How do you deal with small sample size?
2. What happens if your sample size is too small?
3. Which statistical test is used for small sample size?
4. How do you justify a smaller sample size?

How do you deal with small sample size?

The most obvious strategy is simply to sample more of your population. Keep your survey open, contact more potential participants, or consider widening the population.

What happens if your sample size is too small?

Too small a sample may prevent the findings from being extrapolated, whereas too large a sample may amplify the detection of differences, emphasizing statistical differences that are not clinically relevant.

Which statistical test is used for small sample size?

A t-test is necessary for small samples because their distributions are not normal. If the sample is large (n>=30) then statistical theory says that the sample mean is normally distributed and a z test for a single mean can be used. This is a result of a famous statistical theorem, the Central limit theorem.

How do you justify a smaller sample size?

The only aspect a researcher needs to justify for a sample size justification based on accuracy is the desired width of the confidence interval with respect to their inferential goal, and their assumption about the population standard deviation of the measure.