PSYC 2300 Lecture Notes - Lecture 4: Nonprobability Sampling, Stratified Sampling, Systematic Sampling
Document Summary
Collecting data and sampling: general questions about a group of individuals is known as population. Entire set of individuals of interest: types of populations. Group is defined by the researcher"s specific interests. Accessible populations narrow down topic from target populations. Sample: actual research conducted with smaller group known as sample. Set of individuals selected from a population. Sample must be representative if results are to be relevant to population. Applicability of results from sample to population depends on representative sample. Random procedures for producing one outcome from a set of possible outcomes. Exact size of population has to be known and all individuals listed. Each individual/unit must have a specified probability of being selected. Selection process must be unbiased = all individuals/unites must have an equal chance of getting selected: non-probability. Population is (a) not completely known, (b) individual probability is unknown or cannot be computed and (c), procedure is biased. Types of probability methods: simple random sampling (srs)
