ABOUT RESEARCH

1. SAMPLING

2. UNIVERSE AND POPULATION
Refers to the total of items about which
information is required for a particular study
Universe
Refers to the total of all items in a field of inquiry
Population
Slide # 2

3. EXAMPLES
Teachers working at
Schools in South
Africa
Teachers working at
Government Schools in
South Africa
Universe Population
Slide # 3

4. POPULATION
A group of individuals that have one or more
characteristics in common that are of interest
to the evaluator / researcher
 A population is a group of individuals’
persons, objects, or items from which
samples are taken for measurement for
example a population of presidents or
professors, books or students.
Slide # 4

5. SAMPLE
A small proportion of a population selected
for Observation and Analysis
A sample is a finite part of a statistical
population whose properties are studied to gain
information about the whole (Webster, 1985).
Slide # 5

6. Types of population
 Target population : is the set of individuals or
objects for which the researcher wishes to
generalize findings.
 The accessible population: is the portion of the
target population that is available to researcher.
 Sample: it is the subset of population drawn
from the accessible population.

7. SAMPLING
The Sample should be representative
of the population.
Slide # 7

8. SAMPLE
SIZE OF THE
SAMPLE
METHODS OF
SELECTING SAMPLE
Slide # 8

9. INTRODUCTION
Sampling is a process of selecting
representative units of a population for study in a
research. It is the process of selecting a subset of
population in order to obtain information
regarding a phenomenon in a way that represents
the entire population.

10. Sampling is the process of selecting a sample
from the target population. A target population
consists of people or objects meeting the
designated set of criteria of interest to the
researchers. The term target population does not
necessarily pertain to human beings

11. Sampling helps….
 It reduces the time and cost
 It saves labour.
 The quality of study is often better with sampling
than with a complete coverage.
 It provides much quicker results
 Precision and accuracy of data .

12. ADVANTAGES OF
SAMPLING
 Economy in expenditure
 Economy in time
 Greater scope
 Greater accuracy
 Organization of convenience
 Intensive and exhaustive data
 Suitable in limited resources
 Better report

13. DISADVANTAGE OF
SAMPLING
 Chances of bias
 Difficulty in getting representative supply
 Need for specialized knowledge:
 Changeability of units
 Impossibility of sampling:

14. CHARACTERISTICS OF A
GOOD SAMPLE
 Representative: A good sample is one, which
within restriction imposed by its size will reproduce
the characteristics of the population with the
greatest possible accuracy.
 Free from bias and error: It should be free from
error due to bias or due to deliberate selection of
the unit of the sample.
 It should be free from random sampling error.

15. Contin…
 No substitution and incompleteness :There should
not suffer from incomplete coverage of the units
selected unit by some other more convenient in any
way.
 Appropriate sample size: Relatively small sample
properly selected may be much more reliable than
large samples poorly selected. But at same time, it is
very essential that the sample is adequate in size so
that it can become more really reliable.

16. Contin…..
 In the sample, only such units should be included,
which as far as possible, are independent.
 While constructing a sample, it is important that
measurable or known probability sample techniques
are used.

17. THE SAMPLING PROCESS
 Define the population (Target population)
 Specify sampling frame (Accessible population)
 Specify sampling unit (Inclusion & Exclusion
criteria)
 Specify sampling method of
measurement(Probability or non probability)
 Determine sample size
 Specify sampling plan
 Select the sample

18. METHODS OF SAMPLING
Probability
Sampling
Non-Probability
Sampling
Every individual has an
equal chance of being
chosen for study
In this method the
Researcher uses whatever
Subjects are available or
considered significant
Example:
 Random Sampling
 Systematic Sampling
Example:
 Purposive Sampling
 Convenience Sampling
Slide # 18

19. PROBABILITY SAMPLING
E.g.: All Students of a particular Class in a College
1. Simple random sampling
2. Systematic sampling
3. Stratified sampling
4. Cluster sampling
Selecting at random
Selecting every nth case
Sampling within groups of the population
Surveying whole clusters of the population
sampled at random
Slide # 19

20. NON–PROBABILITY SAMPLING METHODS
Convenience sampling within groups of the
population
1. Convenience sampling
2. Voluntary Sampling
3. Quota Sampling
Sampling those most convenient
The sample is self – selected
Slide # 20

21. NON–PROBABILITY SAMPLING METHODS
Building up a sample through informants
4. Purposive sampling
5. Snowball Sampling
Hand – picking supposedly typical or
interesting cases
Slide # 21

22. PROBABILITY
SAMPLING

23. Simple random sampling
The probability of being selected is “known
and equal” for all members of the population
 Blind Draw Method (e.g. names “placed in
a hat” and then drawn randomly)
 Random Numbers Method (all items in the
sampling frame given numbers, numbers
then drawn using table or computer
program)

24. Simple random sampling
 Advantages:
 Known and equal chance of selection
 Easy method when there is an electronic
database
 Disadvantages
 Complete accounting of population needed
 Cumbersome to provide unique designations
to every population member
 Very inefficient when applied to skewed
population distribution

25. Simple random sampling

26. Systematic sampling
 It is formed by selecting every nth item
from the universe where `n` refers to the
sampling interval
 The sampling interval can be determined by
dividing the size of the universe by the size
of the sample to be chosen.

27.  Advantages
 Known and equal chance of any of the SI “clusters”
being selected
 Efficiency..do not need to designate (assign a
number to) every population member, just those
early on on the list
 Less expensive…faster than SRS
 Disadvantages:
 Small loss in sampling precision
 Potential “periodicity” problems
 Its not truly random

29. Stratified sampling
The population is separated into homogeneous
groups/segments/strata and a sample is taken from each. The
results are then combined to get the picture of the total
population.
 Sample stratum size determination
 Proportional method (stratum share of total sample is stratum
share of total population)
 Disproportionate method (variances among strata affect sample
size for each stratum

30.  Advantage:
 More accurate overall sample of skewed
population.
 It is superior to SRS
 Sample can keep small in size with out losing
accuracy
 Characteristic of each stratum can be estimated
and comparison can be done.
 Disadvantage:
 More complex sampling plan requiring different
sample sizes for each stratum
 It is very costly tp prepare a stratifued list of all
members
 Possibility of faulty classification

32. Cluster sampling:
 In this method population is divided into
groups (clusters), any of which can be
considered a representative sample. These
clusters are mini-populations and therefore
are heterogeneous. Once clusters are
established a random draw is done to select
one (or more) clusters to represent the
population

33. Contii…
Cluster sampling means random selection of
sampling units consisting of population elements.
Each such sampling unit is a cluster of population
elements. Then from each selected sampling unit,
a sample of population elements is drawn by
either simple random selection or stratified
random selection

34.  Advantages
 Economic efficiency … faster and less expensive than
SRS
 Does not require a list of all members of the universe
 Disadvantage:
 Cluster specification error…the more homogeneous
the cluster chosen, the more imprecise the sample
results

36. Non-probability
Sampling Methods

37. Convenience samples
 samples drawn at the convenience of the
interviewer. People tend to make the
selection at familiar locations and to choose
respondents who are like themselves

38.  Advantages
 Convenience sampling is the cheapest and simplest
 Does no require a list of population
 Does not require any statistical expertise
 Disadvantages
 Highly biased
 Least reliable sampling method
 Finding cannot generalized

39. Quota Sampling Methods
 It uses a convenience sampling technique with an added feature- a
strategy to ensure the inclusion of subject type likely to be
underrepresented in the convenience sample. The goal of quota
sampling is to replicate the proportions of subgroups present in the
population.
 Technique is similar to that used in stratified random sampling.
 Quota sampling requires that the researcher be able to identify
subgroup I the target population that are important for achieving
representativeness in the problem being studied.

40.  Advantages
 Less costly
 Easy administratively
 It is independent of the existence of sampling frames.
 Disadvantages
 Not possible to estimate sampling error
 Not provide a representative sample respondents
 In this type investigator often selects those
respondents whom he knows.

41. Snowball sampling
 It is also known as nominated sampling, in
which study subject are asked to provide
referrals to other study subjects
 It is also know as network sampling or link-
tracing sampling

42.  Advantage
 It is very useful in studying social groups,
informal group.
 It is useful for smaller population for which no
frames are readily available
 Disadvantage
 Does not allow the use probability statistical
method
 It id difficult to apply for large population
 Does not ensure the inclusion of all elements

43. Judgment or purposive
 samples that require a judgment or an “educated guess”
on the part of the interviewer as to who should represent
the population..
 In sampling in which subjects are selected
because they are identified as knowledgeable
regarding the subject under investigation.

44.  Advantages
 it is very simple to draw
 It is les costly and involves les field work
 It is more representative of typical condition.
 It guarantees inclusion of relevant elements in the
sample
Disadvantage
 it is not always reliable
 Researcher need considerable knowledge about the
population
 Less efficient for generalizing

45. Voluntary sampling
 Is a type of In which volunteers either offer or
are actively participate in a study.
 A request for volunteers might be through an
international organization

46. Expert sampling
 In which the researcher selects study
participants based on the need to ascertain how
expert in a field would react to judge the
phenomena of interest for the study.

47. Event sampling
 in which the investigator is concerned only
with sampling from those specific occurrences
Or events that are relevant to the study.

48. Time sampling
Researcher who are concerned with
collecting data on activities that take place at
specific times of the day or night.

49.  Nature of researcher
FACTORS INFLUENCING
SAMPLING PROCESS

50. Sample size
 It is important step in a sample is to determine the
size of the sample. This involves both statistical and
non statistical considerations
 Resources available
 Nature of study
 Method of sampling followed
 Nature of respondents and other field condition
 Nature of population

51. conclusion

52. Bibliography