Statistics

Simple Random

Measurements from a population is a subset of the population selected in such a manner that every sample of size n from the population has a equal chance of being selected

Stratified Sampling

Divide entire population into distinct subgroups called strata. Strata are based on a specific characteristic (age, income, education level). Draw random samples from each stratum

Systematic Sampling

Number all members of the population sequentially. Then, from a starting point selected at random, includes every kth member of the population in the sample.

Cluster Sampling

Divide entire population into pre-existing segments or clusters. Clusters are often geographic. Make random selection of clusters. Include every member of each selected cluster in the sample.

Multistage sampling

Variety of sampling methods to create successively smaller groups at each stage. Final sample includes clusters

Convenience sampling

Create a sample by using data from population members that are readily available

Observational study

observations and measurements of individuals are conducted in a way that does not change the response or variable being measured

Complete randomized experiment

random process used to assign each individual to one of the treatments

Randomized block experiment

Individuals are first sorted into blocks, then a random process is used to assign each individual in the block to one of the treatments