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Question		Answer
sampling start learning		the process of selecting units from the population of interest
population start learning		the group you want to generalise to and the group you sample from in a study
generalising start learning		the process of making an inference that the results observed in a sample would hold in the population of interest
theoretical population start learning		a group which, ideally, you would like to sample from and generalise to
accessible population start learning		a group that reflects the theoretical population of interest and that you can get access to when sampling
sampling frame start learning		the list from which you draw your sample
sample start learning		the actual units you select to participate in your study
simple random sampling start learning		a method of sampling that involves drawing a sample from a population so that every possible sample has an equal probability of being selected
stratified random sampling start learning		a method of sampling that involves dividing your population into homogeneous subgroups and then taking a simple random sample in each subgroup
systematic random sampling start learning		a sampling method where you determine randomly where you want to start selecting in the sampling frame and then follow a rule to select every x the element in the sampling frame list
cluster (area) random sampling start learning		a sampling method that involves dividing the population into groups called clusters, randomly selecting clusters, and then sampling each element in the selected clusters
multistage sampling start learning		the combining of several sampling techniques
sampling distribution start learning		the theoretical distribution of an infinite number of samples of the population of interest in your study
normal curve start learning		a common type of distribution where the values of a variable have a bell-shaped histogram or frequency distribution
census study start learning		doesn’t pick a sample, tries to study the whole population
respondent-driven sampling start learning		A nonprobability sampling method that combines chain-referral or snowball sampling, with a statistical weighting system that helps com pensate for the fact that the sample was not drawn randomly
response start learning		a specific measurement value that a sampling unit supplies
statistic start learning		a value that is estimated from data
population parameter start learning		the mean or average you would obtain if you were able to sample the entire population
standard deviation start learning		an indicator of the variability of a set of scores in a sample around the mean of that sample
standard error start learning		the spread of the averages around the average of averages in a sampling distribution
sampling error start learning		error in measurement associated with sampling

Sampling

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