Coverage error: The error that can result when the sampling frame doesn’t include everyone in the population.
Measurement error: The error that can result when the survey does not measure what you want it to measure.
Non-random sampling: The act of choosing a sample when each person in the population does not have an equal chance of being selected to be in the sample.
Non-response error: The error that can result when the people who do not respond are different from the people that do respond.
Population: The entire group of people about which you want to know something (e.g., all students on a college campus).
Power: Having an adequate number of responses to accurately describe characteristics, notice relationships between variables, and uncover differences between sub-populations.
Pre-testing: The act of testing a survey before administering it to the sample to ensure that the survey is understood as it was intended and the administration runs smoothly.
Random sampling: The act of choosing a sample when each person in the population has an equal chance of being selected.
Reliability: The consistency of a survey across time and administration methods.
Representativeness: The ability of the respondents to be similar enough to the population so that the results for the respondents would be the same as if the entire population was surveyed.
Response rate: The percentage of people who responded to the survey, calculated by the number of people who completed the survey divided by the number of people who received the survey.
Respondents: The group of people who actually completed the survey.
Salience: When the survey is meaningful to the respondent.
Sample: The group of people selected from the population to which a survey will be administered.
Sampling frame: The list of people of the population from which you will select a sample (e.g., a list of all students enrolled, a phone book, all of the students who have a mail box in the student union).
Sampling error: The error that can result when a sample is too small.
Validity: The accuracy of inferences made from the results of a survey.
Last Updated: 12/19/08