sample size calculator

The calculation boxes below enable you to i) calculate the sample size required in order to achieve a required level of accuracy or ii) calulate the level of accuracy that you wil achieve for a given sample size. The confidence interval is the range about the estimate within which you can be confident that the true survey estimate lies. The confidence level represents the probability that the estimate lies within the confidence interval.

So with a confidence interval of +/- 5% and a confidence level of 95% we can say that there is a probability of 0.95 that the true value of the survey variable lies within +/- 5% of the survey estimate.

The other factor which determines the size of the confidence interval is the survey percentage. This is the percentage who have respondended positively to a survey question eg 40% of people said that they would vote Conservative. The confidence interval is at its widest when the survey percentage is 50%.

Notes:
1. The calculations are based on the assumption that the sample is a simple random sample (SRS). In practice most samples are more complex and there are several design factors that
    may affect the width of the confidence interval. Please see our section on sample design for more details
2. The calculations also assume that the sample size is small in comparison to the population size. The survey population size has little effect on the width of the confidence interval
    providing the sample size is no more than 5% of the population.

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