Chapter 11: Using Samples to provide evidence

Probability sampling
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Terms in this set (11)
Probability sampling
sampling method in which elements in the accessible population have an equal chance of being selected for inclusion in the study. Examples include simple random sampling, stratified random sampling, cluster sampling/multistaging sampling, systematic sampling
Nonprobability sampling
Sampling methods that do not require random selection of elements. Examples include convenience sampling, quota sampling, purposive sampling, theoretical sampling.
You ensure this by making sure that the sample selected has a lot of representative characteristics of the population, ensures accurate data of the population as a whole.
How do you ensure generalizing data to a population?
Homogeneity
the degree to which elements are similar or homogenous
Heterogeneous
the degree to which elements are diverse or not alike
Attrition Rate
dropout rate; loss of subjects before a study is completed; threat of mortality
Power Analysis
a statistical method to determine the acceptable sample size that will best detect the true effect of the independent value
Significance Level
the alpha level established before the beginning of the study
Effect Size
an estimate of how large a difference will be observed between the groups
Data Saturation
in qualitative research, the time when no new information is being obtained and repetition of information is consistently heard
Power AnalysisA statistical method to determine the acceptable sample size that will best detect the true effect of the independent variable