Flashcards · 7357 · Topic 12

K: Statistical sampling flashcards

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Population, sample and census: Population: the whole set of items of interest. Sample: a part of the population from which data are collected. Census: data from every member of the population.
Sampling frame: A list of the population from which the sample is chosen.
Simple random sampling: definition and method: Every sample of size n is equally likely. Number the sampling frame, generate random numbers, ignore repeats and out-of-range values, and stop at n members.
Opportunity sampling: method and drawback: Use whoever is available at the time. It is quick and cheap, but not random and likely to be biased.
Systematic, stratified, cluster and quota sampling in one line each: Systematic: every kth item from a random start. Stratified: random samples from each group in proportion. Cluster: whole groups chosen at random. Quota: set numbers per group, chosen by the interviewer.
Why might two samples from the same population give different conclusions?: Each sample is only part of the population, so sample statistics vary from sample to sample. Conclusions from a sample are informal inferences, not certainties.
Advantages and disadvantages of a census: Advantage: exact information about the whole population. Disadvantages: expensive and slow, and impossible when testing destroys the item.