Sample size calculator

MarketingStat’s representative sample size calculator is a comprehensive and reliable tool. Follow the instructions to use it. At the end of the process you can print the sample size calculator results or you can save them in a PDF file.


How many interviews for a representative sample size?
MarketingStat’s sample size calculator is accurate and
completely free to use.


What do you need a sample for?

Select this option if the survey is supposed to estimate market shares, brand awareness, loyal users, etc. and you want to create confidence intervals around it. For instance, you want to be able to make statements like "the true market share of Brand X falls with, say, 95% confidence in the range 12%±2%".
Select this option if your sample should help to validate hypotheses. For instance, say you stated:
  • H0: Do not launch the new product if (Weekly Sales <= 700 units)
  • H1: Launch the new product if (Weekly Sales > 1'000 units)
What sample size is required to make this decision?
Select this option if you cannot choose one of the options above to calculate the sample size.


When is a survey representative? All surveys are representative. The real question is: Representative of what?

Some believe large samples make surveys representative, but it is not true. Large samples reduce the error level associated with the answers. In fact, at the 95% confidence interval both samples of 96 and 9’512 interviews may be representative of the population they are drawn from. The difference lies in the error level, 10% for the former sample and 1% for the other.

What ultimately makes a representative sample is its ability to reproduce the characteristics of the population it comes from.

This means the way interviewees are selected is what really impacts the ability of a sample to represent the population it refers to.

If our survey is supposed to estimate the median height of Californian women and we measure 9’512 women living in Los Angeles, no matter how large the sample, the survey will not be representative of the Californian women.

The cross-tables of the fix data is usually a good place to start looking for evidence concerning the representativeness of a sample survey.



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