One of the most common questions we get asked by people doing surveys is “How big should my sample size be?”. While there are many sample size calculators and statistical guides available out there, those who never did statistics at university (or have forgotten it all) may find them intimidating or difficult to use.
What Is Sample Size?
Sample size is an often-used term in statistics and market research, and one which inevitably comes up when you’re surveying a large population of respondents. It relates to the way in research is conducted in extremely large populations.
So what exactly is sampling, and why does sample size actually matter?
When you survey a large pool of respondents, you’re interested in the entire group. However, it’s not realistically possible to get answers or results from categorically everyone. So you select a random sample of individuals which characterises the population as a whole.
The size of the sample is quite important for getting accurate, statistically significant results as well as running your study successfully. If your sample is too small, you could include a disproportionate number of individuals who are outliers as well as anomalies. These skew the outcomes and you don’t get a fair picture of the entire population.
If the sample is too big, the entire study becomes complex, expensive and time-consuming to run, and though the results are more accurate, the benefits don’t outweigh the costs.
What Is A Recommended Sample Size?
The sample size that is normally recommended for most market research studies is based upon the industry standard 95% confidence level, that has an accuracy rate of ± 5%.
The term ‘confidence level’ refers to the likelihood that the final results will not deviate by more than a particular percentage from the actual population statistics (i.e., the results obtained if everyone in the population were to be surveyed).