This menu selection is used to determine the maximum error you can expect for a given sample size for research questions involving percents. This is commonly referred to as "sampling error" or "margin of error".

Four questions must be answered to determine the maximum error rate:

1. Best estimate of the population size: You do not need to know the exact size of the population. Simply make your best estimate. An inaccurate population size will not seriously affect the formula computations. If the population is very large, this item may be left blank.

2. Best estimate of the rate in the population (%): Make your best estimate of what the actual percent of the survey characteristic is. This is usually the same percentage that was reported in the study that was conducted. That is, the sample provides the best estimate of the population parameter.

3. Sample size: This is the actual sample size used to represent the population.

4. Desired confidence level (%): How confident must you be that the true population rate falls within the acceptable difference (specified in the previous question)? This is the same as the confidence that you want to have in your findings. If you want 95 percent confidence (typical for social science research), you should enter 95. This means that if you took a hundred samples from the population, five of those samples would have a rate that exceeded the difference you specified in the previous question.

The result will be the maximum difference you would expect at the specified confidence interval. This is generally referred to as the margin of error for a study and is reported as a plus or minus percent. In other words, any percentage reported by the study could be plus or minus the margin of error. The confidence interval describes how certain you are that the actual percentage in the population does not exceed the margin of error.

Example

A manufacturing company conducted a study of 157 respondents. Their report stated that 61.0% of the respondents liked the new product design better than the previous product design. What is the margin of error in their findings if you want to be 95% certain that the actual error doesn't exceed that error?

You might make a statement this: We are 95% certain that the percentage in the population who like the new product design better than the pervious product design is between 53.4% and 68.6%. Alternatively, we could say that if we were to take repeated samples from the population (i.e., do the research over and over again), we would expect the percent to fall within that range for 95% of the samples.