Download Sampling Techniques

Sampling
Techniques
Muhammad Ibrahim Sohel
BBA
Department of Business Administration
International Islamic University Ctg (Dhaka Campus)
Sampling preliminaries
Sampling: Way of taking sample under specific research objectives.
Population: Aggregate or totality of all objects/elements/ individuals about which we wish to make an inference.
Sample: Reperesentative/ selected part from a population.
Sampling frame: List of all possible elements/ units in the population.
Sampling units: Individual units/elements that should be studied under specific research objectives.
Parameter: Summary descriptors ( e.g. Mean, variance, proportion) of variables of interst in the population.
Statistics/ Estimator: Descriptors of population parameters computed from sample.
Estimate: Quantitative / specific values of an estimator obtained from sample.
Census: Count of all the elements/individuals in a population.
Survey: Count of elements elements/individuals in a sample.
Sampling Preliminaries... contd.
Reasons for Sampling:
1. Lower cost.
2. Greater accuracy of results.
3. Greater speed of dta collection.
4. Availability of population elements.
Essentilas of a good sampling design:
Accuracy: Neither over-estimate nor under-estimate the
population parameters.
Precision: Produces the smaller standard error of estimate.
Types of sampling
Element Selection
Representation Basis
Probability
Non-probability
Unrestricted
Simple random sampling
Convenience sampling
Restricted
Complex random
sampling
Purposive sampling
Judgement sampling
Stratified sampling
Quota sampling
Systematic sampling
Snowball sampling
Cluster sampling
Double sampling
Different Probability sampling schemes
Type of Sampling
Description
Simple random sampling
Each population element has an equal chance of being
selecyed into the sample. Samples drawn using random
number table / generator.
(Cost: high
Use: Moderate.)
Stratified sampling
(Cost: High
Use: Moderate)
Systematic sampling
(Cost: Moderate
Use: Moderate)
Cluster sampling
(Cost: Moderate
Use: High)
Double sampling
(Cost: Moderate
Use: Moderate)
Population is divided into some homogenous
subpopulations or strata and samples are taken from each
stratum using simple random sampling. Results may be
weighted and combined.
Selects an element of the populationat the begining with a
random start, and following the samling skip interval selects
every k-th element.
Population is divided into heterogenous sub-groups or
clusters with homogenous elements. Some are randomly
selected for complete enumration.
Process includes collecting data from a sample using a
previously defined technique. Based on the information
found, a subsample is selected for further study.
( Sometimes, it called sequential or multiphase sampling)
Non-probability sampling schemes
Type of sampling
Description
Convenience sampling
Available units/ elements from population consists the
(Normally
easiest
and sample. Researcher or field worker have the freedom to
cheapest but result may be choose whomever they find.
biased)
Judgement sampling
Selection of sample conform with some predetermined
criterion.
Quota sampling
Selection of sample from certain relevant characteristics
that well-describe the dimension of population. (e.g.
Gender, religion, socio-economic class)
Snowball sampling
In the initial stage, individuals are discovered and may
or may not be selected through probability amplong.
This group is then used to refer to others who possess
similar characteristics and who, in turn identify others.
The End