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SAMPLING
Procedure by which some members of a given population are selected as representatives of the entire population.
UNIVERSEthe larger group from which individuals are selected to participate in a study
SAMPLEthe 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
SAMPLE
INFERENCE
Process Of SamplingDefine the Population
Develop Sampling Frame
Select a Sampling Method
Determine Sample Size
Execute the Sampling Process
Define the Population
Develop Sampling Frame
Select a Sampling Method
Determine the Sample Size
Execute the Sampling Process
The Sampling Process
Sampling and representativeness
Sample
Target Population
SamplingPopulation
Target Population Sampling Population Sample
Sampling Techniques
FixedVs
Sequentialsampling
AttributesVs
Variables Sampling
ProbabilityVs
Non-probability sampling
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 Samplin
g
Non-probability Sampling Methods
Convenience Sampling
Judgment Sampling
Quota Samplin
gOther
Sampling
Methods
SIMPLE RANDOM SAMPLINGSimple 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:1. Lottery Method2. 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 investigationsFirst stage- preparation of large sized
sampling units Randomly selecting a certain numberSecond stage- Another list prepared from
themSub-samples drawn by random sampling
CLUSTER SAMPLINGThe process of randomly selecting intact groups, not individuals, within the defined population sharing similar characteristics
Steps :-1. Defined population is divided into number of
mutually exclusive and collectively exhaustive subgroups or clusters
2. Select an independent simple random sample of clusters.
Area SamplingOne 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.
Convenience samplingthe process of including
whoever happens to be available at the time…called “accidental” or “haphazard” sampling.
Purposive samplingthe process whereby
the researcher selects a sample based on experience or knowledge of the group to be sampled…called “judgment” sampling
Quota samplingthe 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 oftarget population Research scope
Statistical analysis needs