How To Calculate Your Ideal Sample Size

Anika Nishat

Anika Nishat

Remesher

Anika is a member of the Remesh marketing team.

In many cases during the course of your market research, you may be unable to reach the entire population you want to gather data about. While larger sample sizes bring you closer to a 1:1 representation of your target population, working with them can be time-consuming, expensive, and inconvenient. On the other hand, small samples risk yielding results that aren’t representative of the target population. 

Luckily, you can easily identify an ideal subset to represent your ideal population and produce strong, statistically significant results that don’t gobble up all of your resources.

Simply, the steps to identify your sample size are as follow:

  1. Define population size
  2. Designate your margin of error
  3. Determine your confidence level
  4. Predict expected variance
  5. Finalize your sample size

Follow these five steps to ensure you get the right sample size for your research needs.

sample size calculation step 1
Define the size of your population

Your sample size needs will differ depending on the population size you’re looking to draw conclusions on. That’s why determining the minimum number of people required to represent your sample is an important first step.

Defining the size of your population can be easier said than done. While there is a lot of population data available, you may be targeting a population that is difficult to measure or for which no reliable data currently exists.

Knowing the size of your population is more important when dealing with relatively small, easy-to-measure groups of people. If you’re dealing with a larger population, take your best estimate, and roll with it. 

sample size calculation step 2 

Designate your margin of error

Random sample errors are inevitable whenever you’re using a subset of your total population. Be confident that your results are accurate by designating how much error you intend to permit: that’s your margin of error.

Sometimes called a confidence interval, a margin of error indicates how much you’re willing for your sample mean to differ from your population mean. It’s often expressed alongside statistics as a plus-minus (±) figure, indicating a range which you can be relatively certain about. 

For example, say you take a sample of your colleagues with a designated 3% margin of error and find that 65% of your office uses some form of voice recognition technology at home. You can be sure that, if you were to ask your entire office, in reality as low as 62% and as high as 68% might use some form of voice recognition technology at home.

sample size calculation step 3
Determine how confident you can be

Your confidence level tells you how certain you can be that the total population would pick an answer within the range you designated in the second step. The most common confidence levels are 90%, 95%, and 99%. Researchers most often employ a 95% confidence level.

Don’t confuse confidence levels for confidence intervals (i.e. mean of error). Remember the distinction by thinking about how the concepts relate to each other.

In our example from the previous step, when you put confidence levels and intervals together, you can say you’re 95% certain that the true percentage of your colleagues who use voice recognition technology at home is within ± 3 percentage points from the sample mean of 65%, or between 62% and 68%.

Your confidence level corresponds to something called a z-score. A z-score is a value that indicates the placement of your raw score (meaning the percent of your confidence level) in any number of standard deviations below or above the population mean.

Z-scores for the most common confidence intervals are:

  • 90% = 2.576
  • 95% = 1.96
  • 99% = 2.576

If you’re using a different confidence interval, use this z-score table to find the right value for your calculation.

sample size calculation step 4
Decide the variance you expect

The last thing you’ll want to consider when calculating your sample size is the amount of variance you expect to see among participant responses. 

Standard deviation measures how much individual sample data points deviate from the average population. 

Don’t know how much variance to expect? Use the standard deviation of 0.5 to make sure your sample is large enough. 


sample size calculation step 5
Discover your ideal sample size

Now that you know what goes into determining sample size, you can calculate sample size online. Or, calculate sample size the old fashioned way: by hand. 

Below, find two types of sample size calculations. One for known population, and one for unknown population.

Sample size for known population

sample size calculation known population

Sample size for unknown population

sample size calculation unknown population

Here’s how the calculations work out for our voice recognition technology example in an office of 500 people, with a 95% confidence level and 5% margin of error:sample size calculation known population

sample size calculation 2

sample size calculation 3

There you have it! 197 respondents are needed.

You can tweak some things if that number is too big to swallow.

Try increasing your margin of error or decreasing your confidence level. This will decrease the number of respondents necessary, but increase chances for errors.

Summing Up Sample Size

Calculating sample size sounds complicated - but, easy formulas for sample (like the ones above) and even calculators are now available to make this tedious part of research faster! 



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