sampling methiod -sujitha
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SAMPLING METHODS
by
R.SUJITHA (MSc.stats
II YEAR)
What is sampling?
Why sampling?
Sampling terms
Purpose of sampling
Methods of sampling
Probability sampling
Non- probability sampling
Application
Limitation
• A process of choosing a representative portion of the entire population.
• It is an integral part of research methodology.
• It involves selecting a group of people, events, behaviors or other elements with which to conduct a study.
WHAT IS SAMPLING?
WHY SAMPLING...Get information about large populations.
More accuracy i.e. Can Do A Better Job of Data Collection.
When it’s impossible to study the whole population.
Less field time.
Less costs.
SAMPLING TERMS...
TARGET POPULATION
STUDY POPULATION
SAMPLE
PURPOSE OF SAMPLINGTo provide various types of
statistical information of a qualitative or quantitative nature about the whole by examining a few selected units.
Scientific procedure of selecting those sampling units which would provide the required estimates with associated margins of uncertainty, arising from examining only a part and not the whole.
CLASSIFICATION OF SAMPLING
sampling
Probability
Simple random
sytematic
Stratified random
cluster
Non- probability
convinience
Quota
Snowball
Judgment
PROBABILITY SAMPLING
A sampling technique in which every member of the population will have a known, nonzero probability of being selected.
Probability sampling includes
Simple Random SamplingSystematic SamplingStratified Random SamplingCluster Sampling
SIMPLE RANDOM SAMPLINGIn this method each item of the data(population) has the same probability of being selected in the sample. The selection is usually made with the help of random numbers.Advantages
minimal knowledge of population neededExternal validity high; internal validity high; statistical estimation of errorEasy to analyze data
DisadvantagesHigh cost; low frequency of useRequires sampling frameDoes not use researchers’ expertiseLarger risk of random error than stratified
SYSTEMATIC SAMPLING
Advantages Moderate cost; moderate usageExternal validity high; internal validity high; statistical estimation of errorSimple to draw sample; easy to verify
DisadvantagesPeriodic orderingRequires sampling frame
An initial starting point is selected by a random process, and then every nth number on the list is selected
STRATIFIED RANDOM SAMPLING Type of probability sampling which
selects members of the sample proportionally from each sub- population or stratum.
Used when the population is too large to handle and is divided into subgroups (called strata)
Samples per stratum are then randomly selected,but considerations must be given to the sizes of the random samples to be drawn from the subgroups.
STRATIFIED RANDOM SAMPLINGAdvantages Assures representation of all groups
in sample population needed
Characteristics of each stratum can be estimated and comparisons made
Reduces variability from systematic
Disadvantages Requires accurate information on
proportions of each stratum.
Stratified lists costly to prepare
CLUSTER SAMPLING
One-stage sampling: All of the elements within selected clusters are included in the sample.Two-stage/multistage sampling:A subset of elements within selected clusters are randomly selected for inclusion in the sample.
• Used when population is divided into groups or clusters• Samples are selected in groups rather than individuals which
is employed into a large-scale survey
Section 4
Section 5
Section 3
Section 2Section 1
CLUSTER SAMPLING
Advantages• Low cost/high frequency of use• Requires list of all clusters, but only
of individuals within chosen clusters• Can estimate characteristics of both
cluster and population• For multistage, has strengths of
used methods
Disadvantages• Larger error for comparable size
than other probability methods• Multistage very expensive and
validity depends on other methods used
CLUSTER SAMPLING
NON- PROBABILITY SAMPLING Involves the selection of elements
from a population using non random procedures.
The members of sample are drawn or selected based on the judgment of the researcher.
The results of these techniques are relatively biased.
The techniques lack objectivity in terms of the selection of samples
The sample are not so reliable. The techniques are convenient and economical to use.
NON- PROBABILITY SAMPLING
Non probability sampling includes
Convenience sampling
Snowball sampling
Quota sampling
Judgment sampling
CONVENIENCE SAMPLING-The sampling procedure involves the nonrandom selection of subjects based on their availability or convenient accessibility
Advantages • Very low cost• Very extensively
used/understood• No need for list of population
elementsDisadvantages• Variability and bias cannot be
measured or controlled. • Projecting data beyond sample
not justified.
QUOTA SAMPLING-The sampling procedure that ensure that a certain characteristic of a population sample will be represented to the exact extent that the investigator desires.
Advantages • low cost• Useful in specific circumstances• Useful for locating rare populations
Disadvantages• Bias because sampling units not independent• Projecting data beyond sample not justified.
SNOWBALL SAMPLING
Advantages • moderate cost• Very extensively used/understood• No need for list of population
elementsDisadvantages• Variability and bias cannot be
measured or controlled (classification of subjects)
• Projecting data beyond sample not justified.
-The sampling procedure in which the initial respondents are chosen by probability or non-probability methods, and then additional respondents are obtained by information provided by the initial respondents
JUDGMENT SAMPLINGThe sampling procedure in which an experienced research selects the sample based on some appropriate characteristic of sample members… to serve a purpose
Advantages • Moderate cost• Commonly used/understood• Sample will meet a specific
objective
Disadvantages• Bias!• Projecting data beyond sample
not justified.
ADVANTAGESGreater economy: The total cost of a sample will be much less than that of the whole lot.
Shorter time-lag: With smaller number of observations it is possible to provide results much faster as compared to the total number of observations.
Greater scope: Sampling has a greater scope regarding the variety of information by virtue of its flexibility and adaptability.
Actual appraisal of reliability
LIMITATIONSErrors due to sampling may be high for small
administrative areas.
Sampling may not be feasible for problems that require very high accuracy.
APPLICATIONSAuto manufacturing industry
Survey about employment and unemployment in the nation
Local housing authority
Local transportation
Journals , magazine.
TV networks etc.,
Thank You…
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