Confidence Level: An indicator of how often the true percentage of the population would pick an answer lying within the confidence interval. For example, 95% confidence level means you can be 95% certain. Most researchers use the 95% confidence level.

Population Size: The exact number of people in the population that you are studying and from which the sample will be drawn.

Margin of Error: Indicates the desired degree of precision attached to an estimate computed from the survey. It indicates the range into which the estimate would fall if the entire population was surveyed. For example, if a 5% margin of error is acceptable to the researcher and the survey estimate of the measured characteristic is 48%, then if the entire population were surveyed, one would expect the true value of the characteristic of interest to lie between 43% and 53%.

Estimated Response Rate: This is an estimate of the percent of the sample that will complete the survey and is usually based on previous experience. For example, 95% response rate assumes that 5% of the people in the sample will not complete the survey because they refused or couldn’t be located or other reasons.

Population Proportion: This is an estimate of the percentage of your sample that will pick a particular response. If most of the respondents will answer in a particular way, for example 90% yes and 10% no, then a smaller sample will suffice, compared to the “worst-case” scenario, where 50% say yes and 50% say no. To ensure an adequate sample size, it is best to assume the worst-case scenario.

Sample Size: This is the number of people out of the entire population of interest that will be selected for the administration of the survey. It is NOT the number of completed surveys to be gathered. Depending on the response rate selected, the sample size estimate includes the number of completed surveys and a percentage of refusals or no contacts.