The entire group of individuals or instances about whom we hope to learn.
A (representative) subset of a population, examined in hope of learning about the population.
A study that asks questions of a sample drawn from some population in the hope of learning something about the entire population.
Any systematic failure of a sampling method to represent its population.
The best defense against bias. Each individual is given a fair, random chance of selection.
Any attempt to force a sample to resemble specified attributes of the population.
The number of individuals in a sample. Determines how well the sample represents the population, not the fraction of the population sampled.
A sample that consists of the entire population.
A numerically valued attribute of a model for a population. We rarely expect to know the true value, but we do hope to estimate if from sampled data.
Values calculated for sampled data. Those that correspond to, and thus estimate, a population parameter, are of particular interest.
A sample is said to be this if the statistics computed from it accurately reflect the corresponding parameters.
Simple Random Sample
Each set of n elements in the population has an equal chance of selection.
A list of individuals from whom the sample is drawn.
The natural tendency of randomly drawn samples to differ, one from another. Sometimes results in Sampling Error.
Stratified Random Sample
A sample design in which the population is divided into several subpopulations, or strata, and random samples are then drawn from each stratum.
A sampling design in which entire groups are chosen at random.
Sampling schemes that combine several sampling methods.
A sample drawn by selecting individuals systematically from a sampling frame.
Voluntary Response Bias
Bias introduced to a sample when individuals can choose on their own whether to participate in the sample.
Consists of the individuals who are conveniently available.
A sampling scheme that biases the sample in a way that gives a part of the population less representation than it has in the population.
Bias introduced to a sample when a large fraction of those sampled fails to respond.
Anything in a survey design that influences responses falls under this.