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What the results mean
This calculator allows you to determine the minimum sample size required to meet the precision requirements of your study. For example, if you expect that 50% of the respondents in your survey will answer a question in a particular way and you want to be 95% certain that the true population proportion estimated by your sample is between 45% and 55% (5% confidence interval), you would need to conduct 384 interviews to meet these precision requirements.
More information
Step 1: Confidence Level
The value chosen in Step 1 determines the confidence level of your results. It tells you how often the true percentage of the population would fall within the confidence interval of results obtained in your survey. For most marketing research studies, a confidence level of 95% is used.
Confidence level is related to the level of significance (α ). A 95% Confidence level corresponds to α = .05. If the Level of significance (α) = .05, that means that there is one chance in twenty that the population value falls outside the Confidence Interval.
Step 2: Estimated Proportion
The value entered here should be your best guess as to what the true population proportion is. If you have no idea, enter 50%, as it is the most conservative value, resulting in the highest estimate of interviews needed.
Step 3: Confidence Interval
The value entered here determines the range of values within which the true proportion will lie, with the certainty as selected in Step 1. The confidence interval is the plus-or-minus figure you usually see reported with survey results.
Assumptions
This calculator assumes that the population size is relatively large. If the sample size is greater than 5% of the population, then the calculation requires a Finite Population Correction factor to be included.
It is also assumed that your sample represents a random sample of the relevant population.
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