The Importance of Sample Size

Whatever market research you’re conducting or survey you’re running in support of it to better understand your consumers, customers or the performance of your products, it’s usually impossible, or at least impractical to collect data from all the people or items that you’re interested in.

Subsequently, researchers will take a sample (or subset) of their population of interest instead and look to see what insights they can learn from that sample, in order to make some presumptions about the behaviours and opinions of their wider and larger target population group.

Why is sample size important in research?

Even before we explore the significance for surveys, the issue of why sample size is important is quickly brought into sharp focus when we consider the well documented importance of sample size in quantitative research and qualitative research.

In quantitative research, the ability to draw conclusions with a reasonable amount of confidence relies on having an accurate sample size calculation, as without this it can lead to results being missed, biased or just plain incorrect. It can also result in rendering a study unethical, unpublishable, or both. And while qualitative research projects don’t usually require as large a sample size as quantitative research, they still need to be large enough to be able uncover the variety of opinion necessary to address their questions and offer findings of valuable enough interest to their area of study.

Benefits of a large sample size

In contrast to its importance in research, when it comes to the importance of sample size in online surveys what we’re referring to is the number of completed responses a specific survey generates.

The general consensus is that the larger your sample size, or higher your volume of survey responses as it’s otherwise known, the more reliable your results will be.

However, it’s not quite as simple as that, as the margins between obtaining or falling short of a statistically significant sample size can be extremely narrow.

For example, if you were running a market research survey in order to discover more about the purchasing habits of sports enthusiasts and their choice of running shoes, and your sample size contained too few responses, it could result in data that is unrepresentative of your target population and inaccurate results that are not sufficient to support your decision making.

In contrast, if your sample size yielded too many responses, the analysis of this data could put a huge strain on your available time and budgetary resources. So, much so that any benefits that your research produced could end up being outweighed by your costs.

Subsequently, before creating a survey, it makes sense that in addition to ensuring you generate the most accurate results possible, you calculate a survey response rate that will also maximise the time and budget available to you.

Sample size calculation

When it comes to how to calculate sample size there are a number of ways in which you could potentially do this including using a sample size from a similar study, doing it manually or using a calculator.

Use a similar study

There are lots studies around, so the chances of finding one similar to your own is relatively high, especially if you use a search tool such as the best academic research databases.

You can use their sample size to create your own. However, it is important to be aware that if the researchers didn’t do their calculations correctly, it could impact the credibility of your study.

Carry out a census

If your target population size is relatively small, you might consider taking a census instead of using a sample. Keeping track of a team of 100 people is relatively easy, so you could conduct a census and create a statistically robust study.

However, if your study involved thousands of people, then it would be almost impossible to survey everyone, let alone make sure each person answered your questions.

Work it out manually

If you have strong maths skills, then you might want to try calculating it manually. There are a number of formulas available to do this including Cochran and Slovin’s.

However, calculating your sample size is difficult, and even statisticians can struggle with these manual calculations. So, for accuracy, we would recommend you using a calculator.

Use a sample size calculator

The sample size calculator offers one of the simplest ways to define your sample size. Fortunately, we’ve created a sample size calculator to help you. And because it allows you to input the data for your population size, confidence level and margin of error, you will be able to calculate sample size with the required accuracy that you need in just a few short simple steps. Try it now, to see how easy it is to use.

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