How to Use the Sample Size Calculator
When it comes to probability surveying, creating a sample size should never be left to guessing or estimates. Instead, it should be based on three criteria:
- The size of your target population: This refers to the total amount of people that are eligible to participate in your survey. For example, a study on Ontario citizens’ sleeping habits would have a population equivalent to that province’s population (13.5 million). In many studies it will be impossible to know how many people make up a population. If this is the case, it is accepted among researchers to use a fake population size of 20,000 or larger.
- Your desired confidence level: Usually placed at a value of 95% in surveying, the confidence level describes how sure you can be that your results are correct. With a 95% confidence level, a researcher can be certain that the value of any sample will fall in the range of the margin of error 95% of the time.
- Your allowed margin of error: Margin of error depicts the random sampling error that is possible in the study. This is important because it is impossible to know whether a sample’s results are identical with the true value of the population. The value allotted to the margin of error describes the range in value that the population may have based on the results in the study. This is always described as a plus or minus value.
For example, most people choose a margin of error 5+/- with a 95% confidence interval. If your results showed that 67% of people love rock music, you could say that you are 95% confident that 62-72% (known as the confidence interval) of your targeted population love rock music.
Though selecting your population size is self-explanatory, choosing a confidence level and margin of error can be a little more difficult. Usually survey researchers will choose a confidence level of 95% (or 99% if more precision is required) and a margin of error of 5+/-. However, if a sample size with these two values is too expensive, you may have to lower your confidence level or raise your allowed margin of error.
The following table identifies how each element of a survey will change a result’s accuracy based on whether its value is increased or decreased:
The Effect Survey Values have on the Accuracy of its Results
|Value Increased||Value Decreased|
|Population Size||Accuracy Decreases||Accuracy Increases|
|Sample Size||Accuracy Increases||Accuracy Decreases|
|Confidence Level||Accuracy Increases||Accuracy Decreases|
|Margin of Error||Accuracy Decreases||Accuracy Increases|
To learn more about calculating sample size click here.