Margin of Error Calculator
The margin of error is an important statistical tool that helps you understand how well a sample may represent a larger population. Simply put, it helps you avoid over-generalizing the findings of a dataset based on the number of samples you have collected. The underlying equation for the margin of error looks like this.
Population Size
This refers to the total size of the population you are studying. For example, if you're running a survey about Canadians aged 30 to 45, the population size would be around 8 million based on the recent population statistics in 2023 (Source).
Sample Size
This refers to the number of samples collected in your survey, or the number of samples you intend to collect.
Sample Proportion (%)
This refers to the proportion of respondents who selected a particular answer in your survey. For example, say you ran a survey and asked respondents about their favourite colour, and 65% said their favourite colour is red. Then your sample proportion would be 65%. You can input this as a percentage below (i.e. 65% and not 0.65).
Confidence Level
Confidence level corresponds to how sure you want to be about your estimates. You can choose between 90%, 95% or 99%, and 95% is most common.
Margin of Error
If you’d like to learn more about how the margin of error is calculated and what it means, you can read this article on my blog.
