Chapter 6 - Sampling Flashcards
(30 cards)
probability sampling
sampling based on a process of random selection that gives each case in the population an equal/known chance of being included in the sample
nonprobability sampling
methods of case selection other than random selection
population
the total membership of a defined class of people, objects, or events
sample
a subset of cases selected from a population
probability
the likelihood that something will occur, which may vary from 0 to 100 percent
random selection
a selection process that gives each element in a population an equal/known chance of being selected
sampling without replacement
sampling procedure where once a case is selected, it’s not returned to the sampling frame
sampling with replacement
sampling procedure where once a case is selected, it’s returned to the sampling frame
probability distribution
distribution of the probabilities for a variable, which indicates the likelihood that each category or value of the variable will occur
sampling error
the difference between an actual population value (%) and the population value estimated from a sample
sampling distribution
a rhetorical distribution of sample results for all possible samples of a given size
standard error
a statistical measure of the ‘average’ sampling error for a particular sampling distribution, which indicates how much sample results will vary from sample to sample
normal curve
a bell-shaped distribution of data that characterizes many variables and statistics, such as the sampling distribution of a proportion or mean (aka normal distribution)
confidence interval
a range (interval) within which a population value is estimated to be at a specific level of confidence
target population
the population to which researchers would like to generalize their results
sampling frame
an operational definition of the population that provides the basis for drawing a sample; ordinarily consists of a list of cases
coverage error
the error that occurs when the sampling frame does not match the target population
simple random sample
every case and every possible combination of cases has an equal chance of being included in sample
stratified random sample
population is divided into strata/variable categories and independent random samples are drawn from each stratum
weighting
procedure that corrects for the unequal probability of selecting one or more segments/strata of the populationc
cluster sampling
population is broken down into natural groupings/areas and a random sample of clusters is drawn (multistage = sample at two or more stages)
nonresponse error/bias
(in survey sampling) error that occurs when nonrespondents differ systematically from respondents
case study
holistic analysis of a single person, group, or event by one or more research methods
convenience sampling
selection of cases that are currently available