1.2 Random samples

simple random sample.

every individual of the population has an equal chance of being selected- no researcher bias. may not reflect diversity

stratified sample

drawn from a population that consists of at least two distinct non-overlapping groups called strata.

Systematic Sampling

the elements of the population are arranged in some natural sequential order. every kth

Cluster Sampling

by dividing the the population in sections (clusters). Then all members of each selected

cluster are included in the sample

Multistage Sampling

Often a population is very large or geographically spread out. In such cases, samples are constructed through a multistage sample design of several stages, with the final stage consisting of clusters.

Convenience Sampling

may be severely biased and should be acceptable only when it is reasonable to believe that there is no systematic difference between the sample

and the population

Sampling frame

the list of individuals from which a sample is selected the sampling frame. Ideally, the sampling frame is the entire population.

• However, not all members of a population may be accessible.

Sampling error

To the extent that sample information does not match the corresponding population information, we have an error

Non-sampling error

the result of poor sample design, sloppy data collection, faulty measuring instruments, bias in

questionnaires, etc