Sampling is used to select a subset of individuals from a population to estimate characteristics of the whole population. There are various sampling designs and terminologies discussed. Random sampling aims to give every unit an equal probability of selection and can be done with or without replacement. The document outlines principles of sampling design, advantages like being economical and accurate, and disadvantages like potential for bias. It also discusses planning sample surveys and determining appropriate sample sizes.

2. Sampling
Designs

3. Sampling
 concerned with selection of a subset of individuals from
within a statistical population to estimate characteristic of
the whole population.
Sample
 a small amount or part of something that shows you
what the rest is or it should be

5. Terminologies
Population- a group of experimental data, persons, etc.
Population Total- the sum of all the elements in the sample
frame.
Population Mean- the average of all elements in a sample
frame or population
Sampling Fraction- the fraction of the population or data
selected in a sample

6.  Random sample- every unit has the same probability of
selection
 Simple random sample
1. Selected without replacement
-no repetitions are allowed
2. Selected with replacement
-repetitions are permitted

7. 4 Principles of Sampling Design
Standardize samples
Replicate (for each combination of time, location, and
any controlled factor)
Establish equal number of suitable Controls
Locate all samples Randomly

8. Advantages of Sampling
Very accurate
Economical in nature.
Very reliable.
 High suitability ratio towards the different surveys.
Takes less time
 In cases, when the universe is very large, then the
sampling method is the only practical method for
collecting the data.

9. Disadvantages of Sampling
X Inadequacy of the samples.
X
X
X
X
Chances for bias.
Problems of accuracy.
Difficulty of getting the representative sample.
Untrained manpower.

10. Planning a Sample Survey
1. Objectives of the survey.
2. Population to be sampled.
3. Data to be collected.
4. Degree of precision to be desired.
5. The questionnaire and the choice of data collectors.
6. Selection of the sample design.

11. 7. Sampling units.
8. The pre-test.
9. Organization of the field work.
10. Summary and analysis of the data.

12. Determination of Sample Size
 tables, and power function charts are well known
approaches to determine sample size.

13. Sampling Design

specifies for every sample, there is a probability of
being drawn
Types of Sampling Design
1. Scientific Sampling
2. Non- Scientific Sampling

14. Scientific Sampling
1. Restricted Random Sampling
A method of sampling is described which is a
compromise between systematic sampling and
stratified random sampling. It has less potential for
bias than systematic sampling and also avoids the
practical problems associated with stratified random
sampling.

15. 2. Unrestricted Random Sampling
This method assumes that each site has an equal
chance of being part of the sample selected. Make a
list of all project sites, perhaps by alphabetical order.
Every project site is given a number.
Random sampling isn’t always the most convenient
method of choosing a sample.

16. Difference between restricted and
unrestricted sampling
Unrestricted sampling occurs when elements are
selected individually and directly from the
population, whereas, restricted sampling occurs when
elements are chosen using a specific methodology as in
probability sampling or complex probability sampling.

17. 3. Stratified random sampling
This method of sampling is sometimes used if there
are wide variations in site performance within a certain
geographic location or type of distribution site (i.
e., health centers or schools). All the sites are grouped
into segments, each having some uniform, easily
identifiable characteristics. Each segment is sampled
separately using unrestricted random sampling methods.

18. 4. Systematic Sampling
A statistical method involving the selection of
elements from an ordered sampling frame.
The most common form of systematic sampling is an
equal-probability method. In this approach, progression
through the list is treated circularly, with a return to the
top once the end of the list is passed.

19. The sampling starts by selecting an element from the list
at random and then every kth element in the frame is
selected, where k, the sampling interval (sometimes
known as the skip): this is calculated as:
where n is the sample size, and N is the population size.

20. 5. Multistage Sampling
A complex form of cluster sampling. Cluster sampling
is a type of sampling which involves dividing the
population into groups (or clusters). Then, one or more
clusters are chosen at random and everyone within the
chosen cluster is sampled.

21. Advantages and Disadvantages
cost and speed that the
survey can be done in
convenience of finding
the survey sample
normally more accurate
than cluster sampling for
the same size sample
X not as accurate as
SRS if the sample is the
same size
X more testing is difficult
to do

22. 5. Cluster Sampling
• It is a sampling technique used when “natural”
but relatively homogeneous groupings are
evident in statistical population.

23. Nonscientific Sampling
• Here, not all of the individuals in a population are given
equal chance of being included as sample
, hence, subjectivity occurs.
• Three types of nonscientific sampling:
1. Purposive Sampling
2. Convenience Sampling
3. Quota Sampling

24. PURPOSIVE SAMPLING
• This type of nonscientific sampling is based on
selecting the individuals as samples according to
the purposes of the researcher as his controls.

25. CONVENIENCE SAMPLING
• Also referred to as haphazard or accidental
sampling.
The process of selecting some people to be part of
a sample because they are readily available, not
because they are most representative of the
population being studied.

26. Examples of Convenience Sampling
• Female moviegoers sitting in the first row of a
movie theater
• The first 100 customers to enter a department
store
• The first three callers in a radio contest

27. QUOTA SAMPLING
• This is one of the most common forms of nonprobability sampling. Sampling is done until
specific number of units (quotas) for various subpopulations have been selected.

28. To choose a Quota Sample:
1. Divide the population into strata or groups of
individuals that are similar in someway that is
important to the response.
2. Choose a separate sample from each stratum.
This does not have to be a random sample.
3. Combine these samples to form a quota sample.

29. GROUP 5
The End