A unit in research subject on meaning of population, sample, sampling, and probability/non-probability methods.

1. Overview
Sampling and Sampling Process
Prof. Rafath Razia

3. What is the Meaning of Overview?
• According to Google, it is “a general review
or summary of a subject”

4. Is sampling used only in research?
• Sampling is part of everyday life.......

5. Population
• A complete set of persons or objects that
possess some common characteristic of
interest to the researcher

6. Population Groups
• Target Population: Entire group (people / objects) to
which the researcher wishes to generalize the
findings
• Accessible / Study Population: The available group
from which the researcher draws the sample
• Conclusions of the study are based on data obtained
from the accessible population, and statistical
inferences should be made only to the group from
which the sample was randomly selected

7. Population Groups and Sampling…….
7
Target Population
Accessible / Study Population
Sample

8. Samples
• Although researchers are always interested in
populations, an entire population is generally not
used in a research study
• In most nursing research studies, a sample or
subset of the population is selected to represent
the population

9. Samples
• When a sample is chosen properly, the researcher is
able to make claims about the population based on
data from the sample alone
• The method of sample selection and the sample size
determine how representative a sample is of the
population

10. Sampling- few terms
• Sampling is the process whereby a researcher
chooses a desired sample
• A single member of a population is called an
element
• The terms population member and population
element are used interchangeably
• Elements or members of a population are selected
from a sampling frame which is a listing of all
members of a population
• Examples: telephone directory, hospital census,
membership / voter list, etc,.

11. Inclusion and Exclusion Criteria
Inclusion criteria are a set of
predefined characteristics
used to identify subjects
who will be included in a
research study
Exclusion criteria are
characteristics that
eliminate a potential subject
from the study to avoid
extraneous effect

12. Uses of Sampling
Get information about large populations
Economical
More accuracy of results
High speed of data collection
Availability of population elements
Less field time
When it’s impossible to study the whole population

13. Few Disadvantages
Knowledge of the Researcher
Selection Bias posses threat to validity of study
Difficulty in getting truly representative sample
Non-cooperation
Inaccessibility
Drop-out

14. Reasons for collecting data from the
entire population
When population size is very small
When resources are extensive
When a very high response rate is
not expected

15. To Summarize Target
Population
Copyright ©2002, William M.K. Trochim

16. Types of Sampling Methods
Probability
Sampling Non-probability
Sampling

17. Probability Sampling
• Involves the use of a random selection process to
select sample from elements of population
• Without the use of random sampling procedures , the
ability to generalize the findings is greatly reduced
• The goal is to examine representative elements
• Inferential statistics may be used with greater
confidence

18. The Term- Random
• Can be confusing
• Dictionary definition suggests something that occurs
haphazardly or without direction
• Random sampling however is a very systematic,
scientific process
• Each population element has a known chance or
probability of being selected
• Selections are independent of each other
• Investigator’s bias does not enter into the selection
of the sample

19. Probability Sampling Methods
Random
Sampling
Process
Simple
Stratified
Cluster
Systematic

20. Simple Random Sampling
• The word “simple” does not mean easy or
uncomplicated
• Simple Random Sampling could be quite
complex and time consuming, especially if a
large sample is desired

21. Simple Random Sampling
• It is a type of probability sampling that
ensures each element of the population has
an equal and independent chance of being
chosen
• This method is generally used in at least one
phase of the other three types of random
sampling procedures

22. Steps of Simple Random Sampling
Identify the
accessible
population
Enumerate all
the elements
of the
population
(development
of sampling
frame)
Select a
method to
choose the
sample
(drawing
numbered
slips, use of
table of
random
numbers,
computer
generated list
of numbers)
Select sample
based on pre-
determined
size

23. Stratified Random Sampling
• Population is divided into subgroups, or strata,
according to some variable of importance to the
research study
• After the population is divided into two or more
strata, sample is selected from each strata using
simple random sampling method
• Example: marijuana usage among students

24. Stratified Random Sampling
Proportionate Disproportionate

25. A Sample Size of 1000
Proportionate
• High School 40%
• Intermediate 30%
• Degree 20%
• Post-graduation 10%
Disproportionate
• High School 25%
• Intermediate 25%
• Degree 25%
• Post-graduation 25%

26. Cluster Random Sampling
• When the population is geographically spread out,
sampling procedures may be difficult, impossible,
time consuming and expensive
• Hence, large groups or clusters become the sampling
units

27. Cluster Random Sampling
• The sample is selected from
clusters in two or more separate
stages
• The approach is also referred to
as multi-stage sampling
• During each phase of sampling
from the clusters, either simple,
stratified or systematic random
sampling may be used

28. Cluster Random Sampling
States
• Regions
• North, North-East, Central, East, West, South
Districts
• Regions / Zones / Hilly / Plain /Coastal / Border
• North, East, West, South
Hospitals
• Public Sector / Private Sector
• Teaching / Non-Teaching / Number of Beds

29. Cluster Random Sampling
• Although cluster sampling may be necessary for large
scale survey studies, the likelihood of sampling error
increases with each stage of sampling
• To compensate for the sampling error when cluster
sampling is used, larger samples should be selected

30. Systematic Random Sampling
• This involves selecting every kth element of the
population, such as every fifth, eighth, or twenty-
first element

31. Steps of Systematic Random Sampling
1
Obtain list
of total
population
(N)
2
Determine
sample size
(n)
3
Determine
the sample
width
(k)
4
Calculate
(k) by N/n
500/50=10
(k)

32. Systematic Random Sampling
• Controversial type of random sampling procedure
• May be classified either as probability or non-
probability sampling method

33. Systematic Random Sampling
• Two criteria are needed to be classified as
probability sampling:
1. Listing of the
population (sampling
frame) must be random
with respect to the
variable of interest
2. The first element or
member of the sample
must be elected
randomly

34. Non-probability Sampling Methods
• Here the sample elements are chosen from
the population by non-random methods
which is likely to produce a biased sample
• The investigator cannot estimate the
probability that each element of the
population will be included in the sample
• This restricts the generalizations that can
be made about the study findings

35. Non-probability Sampling Methods
Convenience
PurposiveQuota

36. Convenience Sampling
• Also referred to as accidental or incidental sampling
• Involves choosing readily available people or objects
for study
• This is probably the most frequently used sampling
method
• Saves time and money

37. Convenience Sampling
Convenience
Familiar
Group
Snowball /
Networking

38. Quota Sampling
• Similar to stratified random sampling
• Involves dividing the population into
homogenous strata
• Selecting sample elements from each of these
strata

39. Quota Sampling
Quota Sampling
• Obtains members through convenience
samples
Stratified Random Sampling
• Involves a random sampling method of
obtaining sample members

40. Purposive Sampling
• Involves handpicking of subjects
• Also called as judgemental sampling
• Subjects are chosen that the researcher believes are
typical or representative, of the accessible population
• Many qualitative research studies use purposive
sampling

41. Nieswiadomy RS., Foundations of Nursing Research
5th Edition Pearson Education 2009

42. Thanks