Objective
1.
Sa
mple definition & its types.
Sample
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Sample: It is a part of the population.
Characteristic of population called
parameter, and of sample called statistics.
The differences between probability and
non probability sampling, the results in
probability can be generalized, and in non
probability sampling can not.
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1. Sample of entities.
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2. Sample of value.
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Types of sample:
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A. Probability sample:
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A.1. Simple random sampling: Each member
of population has an equal possibility of
being chosen for the sample with chance
alone responsible for selection of any
member can be chosen by table of random
number. Simple random sampling ( not
haphazard) selected by the following
methods:
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1. Lottery method.
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2. computer generated random sampling.
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3. Using the random number table.
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A.2. Systematically sample: A random
starting point at the beginning of
sample chosen according to the
predominant selection schedule e.g.
100 students are ranked by age then
begin with 4th students and every 10th
student chosen (4th, 14th, 24th,
…).
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Disadvantages of random and
systematically sampling:
They can`t
ensure that the structure of the sample will
be similar to the structure of the population
regarding certain characteristics (e.g. to
study anemia among medical students, I
might choose males more than females as
a number of sample therefore may no
anemia or less while female anemic
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A.3.Stratified sampling: The population
is divided into sampling unites that
contain individuals and then a random
sample of individuals proportionate to the
size of the sampling unites. E.g. in your
college four classes then chose 20% from
each class.
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A.4. Clustered sampling: The population
is divided into unites (or groups) not
individuals , then a random sample of
these clusters will be chosen, clusters
include e.g. schools, districts, hospitals,
villages, clinics, factories
….
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A.5. Multistage sampling: This
procedure is carried out in phases
(stages) and can involve more than
one of the above sampling
methods. It is used or a very large
number of population. E.g. as if we
study Iraqi people so we divide
them into governments, then
districts, village, and so on.
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B. Non probability sample:
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B.1. Convenience sample: Members of
population are chosen for the sample, or
e.g. If a doctor wants to study typhoid he
will not study each patient with typhoid, but
chose cases that reach him in his clinic.
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B.2. Quota sampling: The composition of
the sample regarding certain
characteristics is decided from the
beginning, & the only requirement is to find
the right number of people to fill these
quotas.
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