NURS 2031H Chapter Notes - Chapter 8: Bernoulli Sampling, Stratified Sampling, Systematic Sampling
28 Jun 2018
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Chapter 8: Sampling
Intro:
· Sampling Frame: a list of all the individuals or units in the population interest; provides a means of assess
to individuals in a population for recruitment into the study.
· In the late 19th and early 20th century, mathematics and statisticians converged and realized that probability
theory can be applied to the study of large populations and through the selection of relatively small
samples and that this sampling mechanism could be used to obtain population level estimates.
· Probabilistic sampling (also called statistical sampling, random sampling or even scientific sampling)
relies on probability theory to describe the odds of an individual being selected in a sample. To describe
the odds of an individual being selected in the sample.
· There are two broad classes of sampling techniques: non-probability and probability sampling.
· Sampling it is a means of selecting a subset of units from a population for the purpose of collecting
information from those units to draw inferences about the population as a whole.
· Non-probability sampling: uses a subjective method of seeking individuals or units from a population. It is
faster, easier and inexpensive. The researcher must assume that the sample is somehow a representative of
the population which is often a risky assumption.
· Probability sampling:
o Involves the selection of individuals or units from population based on the principles of
randomization or chance.
o It is more complex, time consuming and usually more costly.
o Because individuals for the population are randomly selected and each individual’s
inclusion probability can be calculated, reliable estimates can be produced along with
estimates of the sampling error, and inferences can be made about the population.
· How probability samples are selected:
o The design chosen depends on the availability of the sampling frame (that is an extensive
and up-to-date list of all members of the population)
Non-Probability Sampling:
· A method of selecting individuals from a population using a subjective (non-random) method.
· Does not require a complete sampling frame.
· It is easy, fast and an inexpensive way of obtaining data.
· Problem: it is unclear whether or not it is impossible to generalize the results for the sample population
since non-probability sample can result in large biases.
· Due to selection bias in absence of a frame, an individual inclusion probability cannot be calculated for
nonprobability samples, so there is no way of producing reliable estimates or estimates of the precision
(sampling error).
· It is usually used as an alternative to probability sampling.
· Non-probability sampling is usually used to generate ideas
· Non-probability sampling is often used to select individuals and for focus groups and in-depth interviews.
· Non-probability sampling schemas:
1. Haphazard Sampling
o Individuals are selected in aimless, arbitrary manner with little or no planning involved.
o Assumes the population is homogenous: meaning that the whole population is alike in
which an individual may be chosen for the sample.
o “man in the street”
2. Volunteer Sampling
o The respondents are volunteers.
o Volunteers must be screened therefore they match the characteristics suitable for the
purpose of study.
find more resources at oneclass.com
find more resources at oneclass.com
Document Summary
Sampling frame: a list of all the individuals or units in the population interest; provides a means of assess to individuals in a population for recruitment into the study. Probabilistic sampling (also called statistical sampling, random sampling or even scientific sampling) relies on probability theory to describe the odds of an individual being selected in a sample. To describe the odds of an individual being selected in the sample. There are two broad classes of sampling techniques: non-probability and probability sampling. Sampling it is a means of selecting a subset of units from a population for the purpose of collecting information from those units to draw inferences about the population as a whole. Non-probability sampling: uses a subjective method of seeking individuals or units from a population. The researcher must assume that the sample is somehow a representative of the population which is often a risky assumption.
