### Sample

A (representative) subset of a population, examined in hope of learning about the population.

### Sample Survey

A study that asks questions of a sample drawn from some population in the hope of learning something about the entire population.

### Randomization

The best defense against bias. Each individual is given a fair, random chance of selection.

### Sample Size

The number of individuals in a sample. Determines how well the sample represents the population, not the fraction of the population sampled.

### Population Parameter

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.

### Statistic

Values calculated for sampled data. Those that correspond to, and thus estimate, a population parameter, are of particular interest.

### Representative

A sample is said to be this if the statistics computed from it accurately reflect the corresponding parameters.

### Sampling Variability

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.

### Voluntary Response Bias

Bias introduced to a sample when individuals can choose on their own whether to participate in the sample.

### Undercoverage

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.

### Nonresponse Bias

Bias introduced to a sample when a large fraction of those sampled fails to respond.