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SAMPLING TYPES
What is sampling?
Using data to say something make an inference with confidence, about a whole population based on the study of a only a few sample.
A sample is a subset of all the members of a “population” or “universe”.
Population and SamplesPopulation: Subjects of interest
Sample: Subset for whom we have data
Statistical techniques to make conclusions
NON-PROBABILITY
SAMPLING
PROBABILITY SAMPLING
SAMPLING TYPES
1-PROBABILITY SAMPLING
Results may be generalized.
Scientific ,operationally conventient and simple in theory .
Every element in the target population has equal probability of being chosen in the sample form population for the survey being conducted .
Probability Sampling Types
Random Systematic Stratified Cluster
1.1-Random Probability SamplingEver individual or item from frame has an equal chance of being selected
Selection may be with replacement or without replacement
Samples obtained from table of random numbers or computer random number generators (prize bond number)
1.2-Systematic Random SamplingSamples selected by an order from sampling frame
1.3-Stratified Random Sample1. Dividing the population into groups, strata2. Combining samples from each group for
total sample
1.3-STRATIFIED SAMPLING
GROUP 1GROUP2GROUP 3GROUP 4
1.4-Cluster Random Sampling
Population divided into several clusters
It is used during evident of natural grouping
All items in selected clusters can be used
Every element in the universe or sampling frame not have equal probability of being choosen in the sample form
2-Non-Probability sampling
Non-probability sampling does not involve random selection.
Non-Probability SamplingTypes
Convenient Snowball Quota Judgmental
2.1-Convenience sampling
selecting a participant or group of participants based on their availability to the researcher
ExamplesStudents enrolled in the researcher’s classesFourth-grade students in two local, parochial schools to which the researcher has access
2.2-Judgment Sampling
samples that require a or an “educated guess” on the part of the interviewer as to who should represent the population. Also, “judges” (informed individuals) may be asked to suggest who should be in the sample.
2.3-Quota SamplingIn this case respondents are selected according to some fixed quota relating to gender, race, religion etc. e.g. 45% women and 55% men. Used when the researcher cannot use probability sampling procedures but does want a sample that is somewhat representative of the populationSimilar to stratified sampling
2.4-Snowball SamplingA respondent is found that meets the sampling criteria, they are asked for more likely candidates, who are asked for more likely candidates and so on.
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