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🔴Sampling Technique🔴QUICK REVISION🔴Types-Subtypes🔴Detail 🔴medical- paramedical-biology student
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In this video you will learn about sampling techniques in very easy method.
Even though you are medical, paramedical or biological students, you can easily learn about sampling technique.
This is very important topic for examination.
Dr.Rainisha S. Maisuria
Physiotherapist
#Dr.Rainisha S. Maisuria
3. Type of questions
10- different types of sampling techniques in detail with
appropriate example
5- what is probability sampling ? Explain any 3 probability
sampling in detail.
3- need of sampling and criteria of good sample .
3- snow ball sampling
4. SAMPLING
Sampling may be defined as the selection of some part
of an aggregate or totality on the basis of which a
judgement or inference about the aggregate or totality
in made.
Sampling is simply the process of learning about the
population on the basis of a sample drawn from it. Thus
in the sampling technique instead of every unit of the
universe only a part of the universe is studied and the
conclusions are drawn on that basis for the entire
universe.
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5. Universe/population
From statistical analysis point of view, we often refer to
two term- universe and population.
The term universe implies the total of all the items or units
of analysis in the field of proposed research.
The term population implies the total number of items for
which information is sought.
Study of whole population is called ‘census study’
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6. Sample- A sample is that part of the universe which we select
for the purpose of investigation . A sample exhibits the
characteristics of the universe. The word sample literally
means small universe.
7. Needs of Sampling
Census study required sufficient amount of money, time
and resources. An individual researcher who has to work
under restricted time frame and has constrain related to
money and resources prefer to go for sample study.
Sometimes ‘measuring’ or ‘testing’ something destroys unit.
For ex. in certain clinical trials experimental unit has to
die. It is unfeasible to conduct population study for such
cases. Hence one has to go for sample study.
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8. Methods of sampling
Methods of sampling can be grouped under two board
categories —
1— Probability sampling methods or Random sampling
methods
2— Non- probablity sampling methods or non-random
sampling methods.
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9. Probability sampling methods
Probability sampling methods are those in which every item
in the universe has equal chance of being chosen for the
sample.
——-> types of probability sample-
a-Simple random sampling (SRS)
b-Stratified sampling
c-Cluster sampling
d-Systematic sampling
E- Multistage sampling
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10. A- Simple random sampling
Sampling procedure is known as simple random sampling
where the individual units constituting the sample are
selected at random.
Random sampling method of selection assures each
individual element or units in universe and equal chance of
being chosen.
In other words, if in a sample size of n, all the possible
combinations of n elementary items have the same probability
of being included, it is called simple random sampling.
11. Simple random sampling can be used when population
under study is homogeneous in nature.
1. With replacement : selected sampling unit allowed to be
a part of sample more than once.
2. Without replacement : selected sampling unit allowed to
be a part of sample only once.
Selecting a random sampling - a random sample can
generally be selected through the following methods-
1. lottery method
2. Using random number tables
12. ——> Lottery method- In this method, a lottery is drawn by
writing the numbers or the name of various units and
putting them in a container.
They are thoroughly mixed and certain numbers are picked
up from the container and those which are picked up are
taken up for sampling.
13. ——> using random number tables- Use of random number
table is more scientific way to select random sample from
the population. Tables of random numbers are available
which does not depict any kind of numeric pattern.
Researcher can select any page and number on that page
randomly and can decide selection criteria.
14. B—Stratified sampling method
In this method, the universe or the entire population is
divided into a number of groups or ‘strata’ in such a way
that the elements within the strata are homogenous where as
between strata there a heterogeneity.
Further stratas should be mutually exclusive and
collectively exhaustive.
Since the method deals with ‘strata’ therefore it is known as
‘stratified’ sampling.
In this technique, the whole universe is divided into various
groups, certain number of items are taken from each group
at random.
15. C— Cluster Sampling
Sometimes it is more cost-effective to select respondents in
groups (cluster).
Sampling is often clustered by geography or by time periods.
(Nearly all samples are in some sense ‘clusterd’ in time-
although this is rarely taken into account in the analysis)
For instance, if surveying households within a city, we might
choose 100 city blocks and then interview every household
within the selected blocks.
Clustering can reduce travel and administrative costs.
16. D- SYSTEMATIC SAMPLING TECHNIQUE
Systematic sampling is a variation of simple random
sampling.
It requires the universe or a list of its units may be ordered
in such a way that each element of the universe can be
uniquely identified by its order.
A voter list, a telephone directory , a card index system
would all generally satisfy this condition.
suppose there are 5000 cards (and hence, 5000 units of the
universe), and we want a sample of 500.
Obtain sampling ratio k = N/n = 5000/500 = 10
17. We can select the number between (and including) 1 and 10
at random, say 8.
Then we can select the units whose cards are in the
following position : 8,18,28,38,………………928, 1008,
…..4998.
This would be a systematic random sample or commonly
known as a systematic sampling.
18. E- MULTISTAGE SAMPLING
This procedure is generally used in selecting a sample from
a very large population(universe).
As the name suggests in multistage sampling, the selection
of sample is made in different stages.
The original units in to which the universe is divided are
primary units.
Each primary unit that falls into the sample is sub-divided
in to secondary units in preparation for the second stage of
sampling.
In 3-stage sampling , there will be primary , secondary and
tertiary units. Sometimes even four stages are used.
19. NON-PROBABILITY SAMPLING TECHNIQUE
Non-probability sampling methods are those which do not
provide every item in the universe with an equal chance of
being included in the sample.
The selection process is partially subjective.
Non-random sampling is process of sample selection
without the use of randomization.
In other words, a non-random sample is selected on a
basis other than probability consideration such as
convenience, judgement etc.
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20. Non-probability sampling methods are-
1- judgement or purposive or deliberate sampling
2- Convenience sampling
3- snow ball sampling
21. 1- Judgment or purposive or deliberate sampling
In this method of sampling the choice of sample items
depends primarily on the judgement of the researcher.
In other words, the researcher determines and includes
those items in the sample which he thinks are most typical
of the universe with regards to the characteristics of
research project.
For ex., if sample of 100 teachers is to be selected from
University having 500 teachers for analyzing the spending
habits of teachers, the researcher would select 100 teachers
who, in his judgement, are representative of the university .
22. 2- convenience sampling
convenience sampling is commonly known as
unsystematic ,accidental or opportunistic sampling.
According to this procedure a sample is selected according
to the convenience of the investigator.
A convenience sampling may be used in the following
cases-
- when universe is not well defined
- when sampling unit is not clear
- when complete list of the source is not available.
23. 3- Snow ball sampling
Snow ball sampling is a non-probability sampling technique
where existing study subjects recruit future subjects from
among their connections.
This sampling technique is often used in hidden populations
which are difficult for researchers to access; example
population would be drug users, sex workers or HIV patient.
24. A STEP TOWARDS SUCCESS
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