Sample and sample size

1. SAMPLE AND SAMPLE
SIZE
Presented by : Roshni Maurya

2. What is the need for statistics?
Generalization of the results

3. Population:
a set which includes all
measurements of interest
to the researcher
(The collection of all
responses, measurements, or
counts that are of interest)
Sample:
A subset of the population

4. Target Population:
The population to be studied/ to which the investigator wants to
generalize his results.
Sampling Unit:
Smallest unit from which sample can be selected.
Sampling frame
List of all the sampling units from which sample is drawn.
Sampling scheme
Method of selecting sampling units from sampling frame.

5. Get information about large populations
 Less costs
 Less field time
 More accuracy i.e. Can Do A Better Job of
Data Collection
 When it’s impossible to study the whole
population

6. 1. Sampling makes possible the study of a
large, heterogeneous (different
characteristics) population.
- The universe or population to be studied
may be too large or unlimited that it is almost
impossible to reach all of them. Sampling
makes possible this kind of study because in
sampling only a small portion of the
population may be involved in the study,
enabling the researcher to reach all through
this small portion of the population.

7. 2. Sampling is for economy.
- Research without sampling may be
too costly. Sampling reduces the study
population to a reasonable size that
expenses are greatly reduced.
3. Sampling is for speed.
- Research without sampling might be
too time consuming.

8. 4. Sampling is for accuracy.
- If it takes too long a time to cover the
whole study population, there may be
inaccuracy. The research must be
finished within a reasonable period of
time so that the data are still true, valid
and reasonable.

9. 5. Sampling saves the sources of
data from being all consumed.
- The act of gathering data may
consume all the sources of
information without sampling. In
such a case, there is no more data
to apply the conclusion to.

10. 1. If sampling is biased, or not
representative, or too small, the
conclusion may not be valid and reliable.
2. In research, the respondents to a study
must have a common characteristics
which is the basis of the study.

11. 3. If the population is very large and there
are many sections and subsections, the
sampling procedure becomes very
complicated.
4. If the researcher does not possess the
necessary skill and technical knowhow in
sampling procedure.

12.  The sample must be valid.
Validity depends on 2 considerations:
1. Accuracy – bias is absent from the sample
2. Precision – sample represents the
population

13. Actual sample selection can be
accomplished in 2 basic ways:
Purposive selection
Random selection

14. Depending upon the type ; nature of
population ; objectives of investigation;
some commonly used designs are :
 Simple random sampling;
 Systematic random sampling;
 Stratified random sampling;
 Cluster sampling;
 Multiphase sampling;
 Pathfinder surveys;

15.  this type of sampling is one in which each
and every unit in the population of the
inquiry has an equal chance of being
selected ; to be included in the sample.
Selection of unit is determined by chance
only.
o To ensure randomness, foll. methods
are chosen:
Lottery method.
Table of Random Numbers.

16. Simple random sampling

17. 6 8 4 2 5 7 9 5 4 1 2 5 6 3 2 1 4 0
5 8 2 0 3 2 1 5 4 7 8 5 9 6 2 0 2 4
3 6 2 3 3 3 2 5 4 7 8 9 1 2 0 3 2 5
9 8 5 2 6 3 0 1 7 4 2 4 5 0 3 6 8 6

18.  main advantage of this technique of sampling
is that, it is easy to understand and it is easy
to apply too, it assures randomness and
eliminates personal bias.
 disadvantage is that, it is hard to use with too
large a population as selection may be widely
spread that it enhances the cost and time to
collect data.

19. SYSTEMATIC RANDOM SAMPLING
 a technique of sampling in which every kth name in a
list may be selected to be included in a sample.
 also called as interval sampling, there is a gap or
interval, between each selected unit in the sample.
 Formed by selecting one unit at random and then
selecting additional units at evenly spaced interval till
sample of required size has been formed.

20. Sampling fraction
Ratio between sample size and population
size
This method may be selected to obtain a
sample out of pts attending OPD of dental
clinic.
Systematic sampling

21. k ( skip interval )= population size
sample size
population size = 64
sample size = 8
k = 8

22. main advantage is that it is more
convenient, faster, and more economical
disadvantage is that it can be adopted as
long as there is no periodicity of
occurrence of any particular event in
population.

23.  the process of selecting randomly, samples from
the different strata of the population used in the
study.
 This means that a framework is laid down initially,
and the subjects of study in a random sample are
then allotted to compartments of framework.
 .

24. Ex: If it is decided to know prevalence of DMF
teeth in diff. age grps, then the age grps form the
strata and a random sample is to be chosen from
each stratum i.e, age grp.
ADVANTAGE:
contributes much to the representative of the
sample,
provides greater accuracy,
can conc. on wider geographical area.
LIMITATION:
Care of homogeneity in each stratum while dividing
population into strata.

25.  used when the population is so big or the
geographical area of the research is so
large.(population forms natural grps or clusters like
villages , wards block or children of school etc.)
 First a sample of clusters is selected and then all
units in each of selected clusters are surveyed.
 Advantage : Efficiency; less time and cost.
 Disadvantage: reduced accuracy or
representativeness, on the account of the fact that in
every stage there is a sampling error.

26. Section 4
Section 5
Section 3
Section 2Section 1

27.  In this, a part of information is collected
from the sample and a part from sub-
sample.
Adopted when interest is in any specific
disease.
Procedure is less costly; less laborious;
more purposeful.

28. o Method used is a stratified cluster
sampling technique ; includes most
Population subgroups likely to have
differing disease levels ; to cover a
standard number of subjects in specific
index age grp in any one location.

29. Method is suitable for foll. Situation :
Overall prevalence of various oral diseases
affecting the population.
 Imp. variations in disease level, severity and
need for treatment in subgroups of population
 To provide information about severity ,
progression of disease, to give an indication of
increasing/ decreasing levels.

30. An optimum size of sample is to be
considered on basis of foll. factors :
 An approximate idea of estimate of characteristics under
study and its variability from unit to unit in population.
 Knowledge about the precision of the estimate of
characteristic.
 Probability level within which the desired precision is to
be maintained.

31.  Availability of exp. material , resources and other
practical consideration.
 Sample size is calculated by the formula:
 n= Z2 * p * ( 1 – p )
 L2

32. Must result in a truly representative sample
Must result in small sampling errors
Must be viable in context of funds available for
the research study.
Must be such so that systematic bias can be
controlled in a better way.

33. 33

34. • Evaluation of oral health status of a
community.
• Evaluation of health education on oral hygiene.
• Studies on administrative aspects of services like
availability and utilization of oral health facilitates
in the community.
• Advance data from surveys.

35. Biostatistics as a discipline is concerned with
inferring about the behaviour of a population given
evidence from a sample. Depending on the objective
of study any one of methods may be used to select
sample . At times several methods of sampling may
be used in the same study . Sample size has to be
decided before selection of sample.