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The sample size is the number of responses that have been completed by respondents to your survey. It is termed as a sample as it is a representative ‘sample’ of your target audience. Respondents can be chosen at random or selected after careful consideration (factors that determine this can include: race, gender, income, education level, etc.)
Sample sizes are required because it is not possible to survey each and every person in your target demographic. This is why you need to select a sample that represents that demographic as closely as possible. However, the issue with determining sample size is – how big of a sample you need.
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A good sample size for a survey is one that is large enough to provide a representative sample of the population being studied while also being practical and feasible to implement.Â
However, the appropriate sample size for a survey depends on a variety of factors, including the size of the population being studied, the level of precision desired, and the variability within the population.
Generally, a larger sample size will result in more accurate and reliable survey results, but it also requires more resources to collect and analyze data.
While there is no one-size-fits-all answer, here are a few points that can help you assess a good sample size for your survey research:
Remember that these guidelines are not definitive and may vary depending on the research question, the method of data collection, and other factors.
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If your sample size is too large, the complexity of your research increases considerably, which in turn makes it more expensive. It is hard to justify the additional expense.Â
On the other hand, if your sample size is too small, then your research can be influenced by outliers and anomalies, and you don’t get an accurate view of your target audience. This is why you need to keep a few factors in mind while determining sample size.Â
If you already have the key details on hand, then you can use our sample size calculator to figure out what sample size you should be targeting.Â
If you’re starting from scratch, the following tips should come in handy:
To determine the most accurate sample size for your research, there are a few other variables that you need to determine. Let’s take a look at them
This is an estimate of the total number of people you are trying to understand. For example, if you were to take a random sample of people across a country, then that country’s total population is your population size.
This is a percentage that represents how confident you are that the population would select an answer within a predefined range. A 97% confidence level implies that you are 97% sure that results will be between x and y numbers (these are parameters decided by you).
This is also a percentage, and it represents how much one can expect the results of your survey to represent the views of the local population. The lower the margin of error, the more accurate your survey will be.
Related: Margin of Error Calculator
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There are two parts involved in calculating the sample size. Here they go:
1. Determine your z-score
Your confidence level needs to be represented by a z-score. There are common z-scores for commonly used percentages which are as follows:
90% – Z Score = 1.645
95% – Z Score = 1.96
99% – Z Score = 2.576
If your confidence level happens to be different, there are multiple tools available on the internet which can help you calculate your z-score.
2. Use the formula for sample size
You can use the following formula to calculate your sample size manually:
This formula can be used if your population size is very large or unknown.Â
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A few things researchers need to keep in mind while figuring out their sample:
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