Factors that influence sample size
Factor 1: Population
The population comprises all individuals whose opinions or behavior are to be studied.
For a global survey, this number would be enormous, whereas for a customer survey conducted by a small business, it would remain manageable.
Surprisingly, the required sample size remains relatively constant above a certain population size.
Factor 2: Margin of error
The margin of error indicates how much the results may deviate from reality.
A commonly accepted margin of error is between 3% and 5%.
The smaller the margin of error should be, the more participants the survey needs.
Factor 3: Confidence level
A confidence level of 95% means that the results reflect the actual opinion of the population with a probability of 95%.
A higher confidence level requires a larger sample size.
Factor 4: Expected response distribution
If the responses are evenly distributed (e.g., 50% yes and 50% no), more participants are needed than in the case of strongly dominant responses (e.g., 90% yes, 10% no).
How many participants are needed?
The required number can be calculated using statistical formulas or online sample calculators.
A rough guideline for a representative survey:
- 500 to 1,000 people for nationwide surveys
- 100 to 400 people for smaller target groups
- 30 to 100 people for exploratory or internal surveys
For surveys with random selection and a confidence level of 95%, the following applies:
- Approximately 1,067 participants are required for a margin of error of ±3%.
- Approximately 385 participants are required for a margin of error of ±5%.
Conclusion
The ideal sample size depends on the desired accuracy and the size of the population.
While large studies often require several thousand participants, a few hundred are often sufficient for internal or smaller surveys.
Careful planning is important in order to obtain meaningful and reliable results.
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