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Understanding sample size:
How to ensure your survey delivers better results

Market research 04 12
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What is sample size?

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.


What is a good sample size for a survey?

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. 

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:

  • For a population of 10,000 or fewer, a sample size of at least 400 is often recommended.
  • For larger populations, a sample size of at least 1,000 is typically recommended.
  • If the population is highly diverse, a larger sample size may be necessary to capture the variability within the population.
  • If the survey requires analysis of subgroups within the population, a larger sample size may be necessary to ensure that each subgroup is adequately represented.

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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How do you determine the right sample size?

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. 

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. 

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. 

If you’re starting from scratch, the following tips should come in handy:

Step 1: Consider the right variables

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

  • Factor in population size

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.

  • Confidence level in sampling

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).

  • The margin of error

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


Step 2: Calculate sample size

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:

Understanding sample size: How to ensure your survey delivers better results airline customer experience management

This formula can be used if your population size is very large or unknown. 

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A few things researchers need to keep in mind while figuring out their sample:

  • If you wish to increase the sampling confidence level, you’ll need to increase your sample size
  • To achieve a lower margin of error, your sample size must increase as well.

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