# Learning Objectives

Sampling Design

1. Sampling theory focuses on the generalizability of descriptive findings to the population from which the sample was drawn. Researchers must also consider whether statements can be generalized from one population to another.
2. Nonprobability sampling is a method of selection in which the probability of selection of any case, or element, is not known. Such methods include availability samples (of students or other groups), quota samples, and purposive samples.
3. Probability sampling methods rely on a random selection procedure to ensure that there is no systematic bias in the selection of elements. In a probability sample, the odds of selecting elements are known, and the method of selection is carefully controlled. The main types of probability sampling methods are simple random samples, systematic random samples, stratified random samples, and multistage cluster samples.
4. The likely degree of error in an estimate of a population characteristic based on a probability sample decreases when the size of the sample and the homogeneity of the population from which the sample was selected increase. Sampling error is not affected by the proportion of the population that is sampled except when that proportion is large. The degree of sampling error affecting a sample statistic can be estimated from the characteristics of the sample and knowledge of the properties of sampling distributions.