This is the total number of eligible participants randomly selected from the sampling frame of the total population in the survey. The desired sample size is determined by the necessary statistical quality for the survey results. [Note: The total sample size will inevitably be greater than the actual number of completed interviews due to varying response rates and other sources of survey error.]
One type of inaccuracy caused by making inferences about the target population based on the sample. The sampling error is an estimate of how a sample statistic is expected to differ from the population parameter.
This is the list of eligible participants included in the target population. The sample is chosen from the sampling frame.
This is the total unweighted count of all completed interviews, also referred to in iPOLL as the population size.
A statistic which describes the sample. (e.g. If you want to do a survey of New York City Marathon runners, including their finishing times, the average finishing time of the those surveyed would be an example of a sample statistic. Not to be confused with population parameter, which would calculate the average finishing time of all the runners, not just a sample of them.)
A method of selecting elements (or units) from the target population in a way that is representative. Types of sampling include: Simple random sampling, stratified sampling, systematic sampling, and multi-stage cluster sampling.
This term refers to materials and information that has previously been documented. For example, a poll, a press release, a business report.
Simple Random Sample (SRS)
The most common sampling method where each element in the population has an equal chance of being selected.
The document from which survey information was gathered.
A statistic that shows the dispersion of scores in a distribution of scores. It is a measure of the average amount the scores in a distribution deviate from the mean. The more widely spread out the scores are, the larger the standard deviation will be.
Standard Error (of the Mean)
A statistic indicating how much the mean score of a single sample is likely to differ from the mean score of the population. It answers the question, "How good an estimate of the population mean is the sample mean?" (Not to be confused with sampling error)
A number that describes some characteristic of a variable. (e.g. the mean, the standard deviation)
A method of sampling where groups that might not otherwise be equally represented are first divided proportionately into categories ("strata"); then, a sample is randomly selected from each of these categories. (e.g. If you wanted to do a study on hospitals, you'd separate them by size-small, medium-sized, and large hospitals. From there, you would draw samples from each category so that they'd all be equally represented.
This notation pertains to the entire release, report, or study from which the question was taken.
The topic classification(s) that best describe the question. The scheme for this categorization was developed by the Roper Center and contains over 100 subject categories.
In cases where responses are not based on the entire sample, a description of the portion of the sample whose responses are being reported appears here (e.g. women, or those who favor a given policy).
The name of the survey firm or other organization which conducted the research.
A method of sampling where units are selected from the sampling frame by every "nth" unit. (e.g. You have a directory of 100,000 names and you want a sample of 1,000 names. Divide 100,000 by 1,000 to get 100. You will select every 100th name from the directory. Randomly select a number between 1 and 100, say 42, and select every 42nd name in groups of 100 (42, 142, 242, 342, 442.) to complete your sample.