PROBABILITY SAMPLING

BY

BHANUTEJA V.R

Definition

• A sample that selects subjects with a known probability.

• Every unit in the population has equal chances of being selected as a sample unit

• Probability samples are important when one wishes to generalize to the larger population because one knows how to weight the responses to fit the characteristics of the population.

Probability Sampling Techniques

• Random Sampling

• Systematic Random Sampling

• Stratified Random Sampling

• Cluster Random Sampling

• Multi-Stage Sampling

• Area Sampling

Random Sampling

• This involves selecting anybody from the sample frame entirely at random.

• Random means that each person within the sample frame has an equal chance of being selected.

• In order to be random, a full list of everyone within a sample frame is required.

• Random number tables or a computer is then used to select respondents at random from the list.

Random Sampling

Systematic Random Sampling

• This selection is like random sampling but rather than use random tables or a computer to select your respondents you select them in a systematic way.

• E.g. every third person on the college list is selected.

Systematic Random Sampling

Stratified Random Sampling

An appropriate group is decided upon i.e. female, male, 15 –18 year olds and the participants are picked randomly from within the state

Stratified Random Sampling

Cluster Random Sampling

• Similar to stratified sampling but the groups are selected for their geographical location

• i.e. school children within a particular school.

• The school is the cluster with the children being selected randomly from within the cluster

Cluster Random Sampling

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