 # SAMPLING TECHNIQUES.

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SAMPLING TECHNIQUES

SAMPLING Procedure by which some members of a given population are selected as representatives of the entire population.

UNIVERSE the larger group from which individuals are selected to participate in a study SAMPLE the representatives selected for a study whose characteristics exemplify the larger group from which they were selected

PURPOSE OF SAMPLING To gather data about the population in order to make an inference that can be generalized to the population POPULATION INFERENCE SAMPLE

Process Of Sampling Define the Population Develop Sampling Frame
Select a Sampling Method Determine Sample Size Execute the Sampling Process

The Sampling Process Define the Population Develop Sampling Frame
Select a Sampling Method Determine the Sample Size Execute the Sampling Process

Sampling and representativeness
Sample Sampling Population Target Population Target Population  Sampling Population  Sample

Sampling Techniques Fixed Attributes Vs Vs Sequential Variables
Probability Vs Non-probability sampling

NON-PROBABILITY SAMPLING
Every element in the target population or universe [sampling frame] has equal probability of being chosen in the sample for the survey being conducted. Scientific, operationally convenient and simple in theory. Results may be generalized. NON-PROBABILITY SAMPLING Every element in the universe [sampling frame] does not have equal probability of being chosen in the sample. Operationally convenient and simple in theory. Results may not be generalized.

CLASSIFICATION OF SAMPLING TECHNIQUES
Sampling Methods Probability Sampling Methods Simple Random Sampling Stratified Random Sampling Systematic Random Sampling Multistage Random Sampling Cluster Sampling Area Sampling Non-probability Sampling Methods Convenience Sampling Judgment Sampling Quota Sampling Other Sampling Methods

SIMPLE RANDOM SAMPLING
Simple random sampling is a method of probability sampling in which every unit has an equal non zero chance of being selected for the sample. Methods of selecting random sample: Lottery Method Tables of Random Numbers

STRATIFIED RANDOM SAMPLING
Stratified random sampling is a method of probability sampling in which the population is divided into different subgroups and samples are selected from each of them. Steps:- All units of population are divided into different stratas in accordance with their characteristics. Using random sampling, sample items are selected from each stratum.

Systematic Random Sampling or Quasi-Random Sampling
Systematic random sampling is a method of probability sampling in which the defined target population is ordered and the 1st unit of sample is selected at random and rest of the sample is selected according to position using a skip interval (every Kth item) K = N n Where, K = Sampling/ Skip interval N = Universe/ Population Size n = Sample Size

MULTISTAGE RANDOM SAMPLING
Used in large scale investigations First stage- preparation of large sized sampling units Randomly selecting a certain number Second stage- Another list prepared from them Sub-samples drawn by random sampling

CLUSTER SAMPLING Steps :-
The process of randomly selecting intact groups, not individuals, within the defined population sharing similar characteristics Steps :- Defined population is divided into number of mutually exclusive and collectively exhaustive subgroups or clusters Select an independent simple random sample of clusters.

Area Sampling One special type of cluster sampling is called area sampling, where pieces of geographical areas such as districts, housing blocks or townships are selected. Area sampling could be one-stage, two-stage, or multi-stage. Generally used by Govt. agencies and agricultural statistics.

Non-probability Sampling Methods

Convenience sampling the process of including whoever happens to be available at the time…called “accidental” or “haphazard” sampling.

Purposive sampling the process whereby the researcher selects a sample based on experience or knowledge of the group to be sampled…called “judgment” sampling

Quota sampling the process whereby a researcher gathers data from individuals possessing identified characteristics and quotas

Other Non-probability Sampling Methods
Intensity sampling: selecting participants who permit study of different levels of the research topic Homogeneous sampling: selecting participants who are very similar in experience, perspective, or outlook Criterion sampling: selecting all cases that meet some pre-defined characteristic Snowball sampling relies upon respondent referrals of others with like characteristics

Factors to Consider in Sample Design
Research objectives Degree of accuracy Resources Time frame Knowledge of target population Research scope Statistical analysis needs

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