casonjc1's version from 2015-06-23 21:31


Question Answer
Four sampling/population units1. population- the entire aggregate of cases we are interested in.
2. Target - the aggregate of cases in which the researcher would like to generalize
3. Accessible population- cases in the population we have access to
4. Sample-a subset the population of the accessible population chosen to represnt
What are the important considerations in a quantiative sampling plantheir representativeness and size. A representatie sample is one whose key characteristics closely approximate that of the population
Probablity sampling1. Simple random sampling- a sample frame is established then a sample is taken at random from that.

2. Stratified random sampling- population is divided into strata to enhance representativeness population is placed in homogeneous subsets

3. Multistage cluster -a form of sampling in which large groupings (clusters) are selected first (nursing schools) typically with successive subsampling of smaller units (nursing students) in a multistage approach FOR LARGE SAMPLES

4. systematic sampling...every third person
Non probablity sampling: Practical weakness: strong potential 4 bias1. Quota- sampling where quotas for certain sample characteristics are established to increase the representativeness of a sample.

2. Consecutive recruiting-all the people from accessible population who meet the criteria over a specific time period for a certain sample size.

3. Purposive(judgmental) -uses researchers knowledge about the population to select sample members
What type of analysis is requires to estimate sample sizePower analysis
Why is power analysis importantan adequate sample size is important to support the hypothesis even when the hypothesis is correct without an adeauqte sample size ti will underimine statistical conclusoin validity

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