PROBABILITY AND SAMPLING ERROR:
Introduction:
What is sampling?
A process of selecting a group of people, events, behaviours or other
elements that are representative of the population being studied are term as
sampling.
Sampling is a pretty old idea, since times immemorial people have examined
a handful of grains to ascertain the quality of entire lot. A housewife
examines only two or three grains of boiling rice to know whether the pot of
rice is ready or not. A doctor examines a few drops of blood and draws
conclusions about the blood constitution of the whole body. A businessman
places orders for materials examining only a small sample of the same. A
teacher may put questions to one or two students and find out whether class
as whole is following the lesson.
Sampling is the process of selecting representative units of a population for
study in a research. It is the process of selecting a subset of a population
inorder to obtain information regarding a phenomenon in a way that
represents the entire population.
What is sampling error?
Difference between a sample statistic used to estimate a parameter and the
actual but unknown value of the parameter.
Sampling error (standard error)
Sampling error refers to the discrepancies that inevitably occur when a small
group is selected to represent the characteristics of a larger group
(population).
A basic idea underlying the use of inferential statistics is that a sample of
events or observations is selected to represent a larger population of those
same events or observations. The sample is intended to reflect as closely as
possible the characteristics of larger population. For example nurse
investigators might collect data on every patient diagnosed with breast
cancer throughout the country to try to understand the effects of a particular
intervention on self-esteem following a mastectomy. This process would be
costly and time consuming and would probably not be feasible given various
financial constraints. Another approach would be to select a sample of
patients diagnosed with breast cancer and infer the results of the
investigation to the larger population.
Whenever a sample is drawn from a larger population (even if even if
random selection is used), that sample cannot exactly duplicate all the
characteristics of the larger group. The means and standard deviations
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