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The confidence interval increases the closer the percentage is to 50%.In survey 1 (above) the confidence interval for a value of 50% is 3.02.
This confidence interval would fall to 0.6 if the survey returned a value of 99% or 1%.
It is important that the survey sample size is considered for statistics where 50% of the population answer both ‘yes’ and ‘no’ as this is when the confidence level is broadest and so provides the general level of accuracy for a sample.
Statistical analysis can be complex, and this article aims to explain some of the basic considerations, to an audience without an assumed mathematical background.
At the end of this article there are a wide variety of links to further reading, which can help you through the process of statistical analysis.
See the section on quantitative surveys for further discussion on populations and samples.
We make inferences (conclusions) about a population from a sample taken from it, therefore it is important that population and sampling is well understood, as any error will influence your inferences (conclusions).
In social science, results with a 95% confidence level are accepted as significant.
The confidence interval is affected by three factors.
The relationship between the confidence interval and sample size is not linear.
An example can be found below: The confidence interval is also determined by the percentage of the sample that provides the same answer.