It is important to be able to accurately test and make assumptions about how a certain population will react to a certain piece of content, product, or service. In order to save time and resources, it is important to be able to gather relevant data from a subset of a specific population which is representative of the larger population.
Using a Sample Size Calculator is important because it allows you to quickly calculate the right population size to use to gather a sample data set which will be relevant for your test. For instance, using such a calculator would allow you to determine how many interviews you need to conduct to get accurate results that reflect a target population as precisely as needed.
In order to make the most use of the Sample Size Calculator, it is important to understand two key terms: confidence interval and confidence level.
- Confidence interval: The confidence interval is often referred to as the “margin of error” and it is the plus or minus number reported in the news in relation to public opinion polling. This represents the percentage range of the population that a pollster can be “sure” would answer this way if the entire population was surveyed.
- Confidence level: The confidence level is the level at which one can be sure that the true percentage of the population would pick the answer within the confidence level. This is typically a confidence level between 95% and 99%.
Before using the calculator, it is important to understand exactly what data points influence the output of the sample size calculator. These are:
- Total population size
- Sample size
- Percentages (confidence interval & confidence level)
Once the user understands these concepts, it is possible to plug the relevant data into the calculator and come to an assessment of an estimated sample size for any test, or determine the confidence interval and levels for a predetermined data sample.