CH6 Sampling Strategies Flashcards
the entire set of individuals or other entities to which study findings are to be generalized
population
a summary description of a given variable in a population
parameter
a number that characterizes some quantitative aspect of a population; a “true” value/measurement
population parameter
a subset of a population used to study it
sample
the summary description of a variable in a sample; used to estimate a population parameter
statistic
a list or a source of all the individuals, items, or elements that are part of the population being studied in a research project or survey.
sampling frame
the process of deciding what or whom to observe when you cannot observe or analyze everything or everyone
sampling
a sample chosen via random selection; characteristics include random change and selection can be calculated
probability sample
a study that includes data on every member of a population
census
a sample not drawn from random selection
nonprobability sample
nonprobability sample where cheapest and easiest observations are selected
convenience sample
the difference between the estimates from a sample and the true parameter that arise due to random chance
sampling error
the amount of uncertainty in an estimate; how close estimate comes to population parameter
margin of error
a set of estimates observed from a large number of independent samples of the same size and drawn from the same method
sampling distribution
the probability that an estimate includes the population parameter (conventionally 95%)
confidence levels
type of probability sample in which each individual has the same probability of being selected
simple random sample
probability sampling where samples are chosen by fixed intervals (e.g. every nth person)
systematic sample
when a random sampling sequence varies in some regular, periodic pattern
periodicity
probability sampling in which target populations are divided into clusters or groups, first selecting clusters randomly, and then individuals within those clusters
cluster sampling
Sampling advantages:
- can take probability samples when sampling frame doesnʻt exist
- more surveys can be conducted at a lower cost
cluster sampling
probability sampling where population is divided into strata and sample members are selected in strategic proportions from each group
stratified sampling
probability sampling which ensures all groups are included; groups are stratified and samples randomly from within the strata
stratified random sampling
sampling from a strata in exact proportions
proportionate stratified sampling
when the proportion of each stratum is intentionally varied from population
disproportionate stratified sampling
a group deliberately sampled at a higher rate than its frequency in population
oversampling
elements selected because they are available and easy to find
availability sampling
when sample elements are selected for a purpose because of their unique position
purposive sampling
a purposive sample that targets individuals who are particularly knowledgeable about certain issues being studied
key informant survey
first point of contact research has with their study population
key informant
when new materials fail to yield new insights only reinforce what is already known
saturation
sampling useful for hard to reach populations with no sampling frame, but members are somewhat interconnected
snowball sampling
sample that consists of whoever or whatever is available without concern of similarity to population of interest
quota sampling
research where scientists study a large number of cases but gather limited amounts of data or variables of each
variable-oriented research
research where scientists gather large amounts of data about a single or small number of cases
case-oriented research
