SAMPLING METHODS AND TECHNIQUES

PREPAIRED BYMS. RAJNI BALA M.LIB,M.PHIL.

DEPTT. OF LIBRARY & INFORMATION SCIENCEKURUKSHETRA UNIVERSITY, KURUKSHETRA

KEY TERMS OF SAMPLING POPULATION SAMPLING SAMPLE QUALITIES OF GOOD SAMPLE TYPES OF SAMPLING PROBABILITY SAMPLING NON PROBABILITY SAMPLING

POPULATIO

All item in any field of inquiry is called a population. It can be any

Institute, Group, Student, Company, University library etc.

SAMPLING The process of selecting a sample

from a population using special sampling techniques called sampling. It should be ensured in the sampling process itself that the sample selected is representative of the population.

Sample Sample is a small section

of population. The sampling is a common

activity in our day to day work

SAMPLE VS. POPULATION

PopulationSample

DEFINITION OF SAMPLING Sampling design in fact means the joint processor

to selection and estimation. It should be

such error of estimation is minimum

QUALITIES OF GOOD SAMPLING

A Good Sample is true A good sample maintains accuracy. A good sample is comprehensive in nature A good sample free from bias. A good sample also economical The subjects of good sample are easily

approachable A good sample makes the research work more

feasible. A good sample has the practicability for research

situation.

TYPES OF SAMPLING

• . Probability sample – a method of sampling that uses of random selection so that all units/ cases in the population have an equal probability of being chosen.

• Non-probability sample – does not involve random selection and methods are not based on the rationale of probability theory.

TYPES OF PROBABILITY SAMPLING Simple Random Sampling Systematic Sampling Stratified Sampling Cluster Sampling Multi-Stage Sampling

SIMPLE RANDOM SAMPLING

Random selection is a sampling method in which each and every item has an equal chance of selection.

SYSTEMATIC SAMPLING This is a selection method in which one or

two items are selected randomly, but other items are selected by adding the average sampling interval to the item selected randomly

STRATIFIED SAMPLING When the population is divided into different

strata's or groups and then samples are selected from each stratum by simple random sampling procedure, we call it as stratified random sampling

CLUSTER SAMPLE The population is divided into subgroups

(clusters) like families. A simple random sample is taken of the subgroups and then all members of the cluster selected are surveyed

MULTI-STAGE SAMPLING

Multistage refer to sampling plans where the sampling is carried out in stages using smaller and smaller sampling units at each stage

TYPES OF NON-PROBABILITY SAMPLING

1.Accidental Sampling Accidental sampling is also based upon

convenience in accessing the sampling population. In which involves the sample drawn from that part of the population which is close to hand.

2.PURPOSIVE SAMPLINGWe actually choose whom to involve in a sample.In purposive sampling, we sample with a purpose in mind. We usually would have one or more specific predefined groups we are seeking.

Quota SamplingIn quota sampling, you select people non randomly according to some fixed quota.

The population is divided into cells on the basis of relevant control characteristics.

50 women, 50 men

The problem here (as in much purposive sampling) is that we have to decide the specific characteristics on which you will base the quota. Will it be by gender, age, education race, religion, etc.?

Thanks