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James Tattersfield
Founding Board Member at Researchos
Managing Director @PolarInsight. Fellow @zincvc. Global Shaper @wef. Endlessly curious.
Highlights
The Magic Number: Determining the ideal sample size for your research 👇
When it comes to research, sample size is a critical factor - get it wrong, and your insights could be skewed or unreliable. But how exactly do you determine the right number of participants, whether you're conducting qualitative or quantitative studies?
For quantitative research, the general rule of thumb is that larger sample sizes produce more statistically significant results. However, bear in mind that there are diminishing returns.
For a confidence level of 95% and a margin of error of 5% (for most decisions this is more than sufficient), here's how the required sample size breaks down:
Population of 1,000 → Sample size of 278 Population of 10,000 → Sample size of 370 Population of 1,000,000 → Sample size of 384
The sweet spot tends to be around 300-400 participants - going much higher than 400 usually won't move the needle significantly in terms of statistical power.
But how about qualitative research?
While quantitative research relies on large, representative samples, qualitative studies aim for depth over breadth.
The goal here is to uncover rich, nuanced insights - not necessarily reach statistical significance.
Most qualitative researchers recommend a sample size of 15-30 participants.
This range allows you to reach "thematic saturation" - the point where new interviews start yielding diminishing returns and repeating the same core themes.
Anything less than 10-15 participants, and you risk missing key insights. Conversely, going beyond 30 participants often doesn't add substantially more value.
The bottom line? There's no one-size-fits-all answer and the level of confidence you need is going to be influenced by many factors specific to the setting you're in.
Understanding these guidelines, however, can help you design research that's both impactful and efficient. And, at the end of the day, isn't that what we're all after?
#Research #Innovation #Strategy #Qualitative #Quantitative #Insight
As in Design and Development, #ResearchOps (Research Operations) is crucial for efficient and effective evidence gathering and analysis work.
How does your organisation measure up when it comes to finding the right participants for your research projects?
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