An event is this if we know what outcomes could happen, but not which particular values will happen.
These are hard to generate. Nevertheless, several Internet sites offer an unlimited supply of these.
This models random events by using random numbers to specify event outcomes with relative frequencies that correspond to the true real-world relative frequencies we are trying to model.
The sequence of several components representing events that we are pretending will take place.
Values of the this record the results of each trial with respect to what we were interested in.
A study that asks questions of a sample drawn from some population in the hope of learning something about the entire population.
The best defense against bias is this, in which each individual is given a fair, random chance of selection.
Any attempt to force a sample to resemble specified attributes of the population is a form of this. It may help make better samples, but it is no substitute for randomizing.
A sample is said to be this if the statistics computed from it accurately reflect the corresponding population parameters.
Simple Random Sampling (SRS)
This is when a sample size, n, is one where each set of n elements in the population has an equal chance of selection.
The natural tendency of randomly drawn sample to differ, one from another. Sometimes called Sampling Error, but it's not an error at all, just the natural results of random sampling.
Stratified Random Sample
A sampling 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.
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 fail to respond.