TYPES OF PROBABILITY SAMPLING

1. PURE / RANDOM SAMPLING

Easy to UNDERSTAND

➢ Easy to APPLY

SYSTEMATIC SAMPLING

A strategy for selecting the members of the sample that allows only CHANCE and a SYSTEM to determine inclusion in the sample.

SYSTEMATIC SAMPLING

A SYSTEM is a PLANNED STRATEGY after a starting point is selected at random.

SYSTEMATIC SAMPLING

MORE CONVENIENT, FASTER, more ECONOMICAL sampling technique.

SYSTEMATIC SAMPLING

Subjects or names are arrayed or arranged in some SYSTEMATIC or LOGICAL manner

STRATIFIED RANDOM SAMPLING

Researcher divides the population into TWO or MORE STRATA on the basis of one or more characteristics

STRATIFIED RANDOM SAMPLING

Each stratum is treated like a DIFFERENT population and a SIMPLE RANDOM SAMPLE is drawn from each

STRATIFIED RANDOM SAMPLING

The sub-samples are then COMBINED to FORM the TOTAL SAMPLE

PURPOSIVE/ DELIBERATE

A CRITERIA or PURPOSE for selection become the BASIS for identifying the respondents/ subjects.

SAMPLING BY REGULAR INTERVALS

Select the cases at REGULAR INTERVALS from a series, alphabetical, or any other arbitrary arrangement.

CLUSTER SAMPLING

Sometimes referred to as an AREA SAMPLING because it is frequently applied on a GEOGRAPHICAL BASIS

CLUSTER SAMPLING

General procedure is to DIVIDE an area of population into CLUSTER or BLOCKS and then within the final cluster APPLY any of the different methods in selecting a sample

CLUSTER SAMPLING

Occurs when you select the members of your sample in CLUSTER rather than in using separate individuals.

NON-PROBABILITY SAMPLING

The sample is NOT a PROPORTION of the population and there is NO SYSTEM in selecting the sample.

NON-PROBABILITY SAMPLING

SELECTION depends upon the SITUATION.