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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