What is sampling? What are the different methods of sampling?My posted question is related with Research Methodology

Sampling refers to the statistical process of selecting
and studying the characteristics of a relatively small number of items from a relatively
large population of such items,, to draw statistically valid inferences about the
characteristics about the entire population.

There are two
broad methods of sampling used by researchers, nonrandom (or judgment) sampling and
random (or probability) sampling. In judgement sampling the researcher selects items to
be drawn from the population based on his or her judgement about how well these items
represent the whole population.The sample is thus based on someones knowledge about the
population and the characteristics of individual items within it. The chance of an item
being included in the sample are influenced by the characteristic of the item as judged
by an expert selecting the item. A judgement sampling system is simple and less
expensive to use. Also when there is very little known about the population under study
a pilot study based on judgement sample is carried out to permit design of a more
rigorous sampling system for a detailed study.

In random
sampling, individual judgement plays no part in selection of sample. Each item in the
sample stands equal chance of being included in the sample. In case of random sampling,
the researcher is required to use specific statistical processes to ensure this equal
probability of every item in the population. A random sampling system enables more
reliable results of statistical analysis with measurable margins of errors and degree of
confidence.

To improve the cost effectiveness of data
collection and analysis, several variations of the random sampling are used by
researchers. Some of the most common types of random sampling methods are (1) simple
random sampling, (2) systematic sampling, stratified sampling, and (4) cluster
sampling.

Simple random sampling ensures that each possible
sample has an equal probability of being selected, and each item in the entire
population has an equal chance of being included in the
sample.

In systematic sampling the items are selected from
the population at a uniform interval defined in terms of time, order or space. For
example an observation may be made every half an hour, or from a long queue of people
every fourth person may be selected, or in a bunch of documents every tenth document may
be selected.

In stratified sample the entire population is
divided in relatively homogeneous group. For example all the students of a school may be
divided in groups of boy and girls. Once this is done random sample from each of such
groups is drawn independently. This approach is suitable when there ate identifiable
sub-groups exist within the population that differ significantly in respect of
characteristic under study.

In cluster sampling the
population is divided into groups or clusters, a sample of these clusters may be drawn.
For example, a city may be divided in a cluster of small localities, and a sample of
these localities may be drawn using random sampling methods. The all the households
within each of the locality may be studied for the research. A research based on a well
designed cluster sampling can often give better result than a research based on simple
random sample with same time and cost of research.