SAMPLING POWERPOINT.pptx popoulation samapling

SAMPLING
PRESENTED BY
Haseeb
CMS ID 59989
SEMESTER 5th
A

INTRODUCTION
Sampling is the process of selecting observations
(a sample) to provide an adequate description
and inferences of the population.
 Sample
 It is a unit that is selected from
population
 Represents the whole population
 Purpose to draw the inference
 Why Sample???
 Sampling Frame
Listing of population from which a sample is chosen

SAMPLING
Population
Sample
Sampling
Frame
Sampling Process
What you
want to talk
about
What you
actually
observe in
the data
Inference

IF THE POPULATION IS
HOMOGENEOUS

IF THE POPULATION IS
HETEROGENEOUS

SIMPLE RANDOM SAMPLING
 All subsets of the frame are given an equal
probability.
 Random number generators

SIMPLE RANDOM
SAMPLING
Advantages:
 Minimal knowledge of
population needed
 Easy to analyze data
Disadvantages:
 Low frequency of use
 Does not use researchers’ expertise
 Larger risk of random error

STRATIFIED RANDOM
SAMPLING
 Population is divided into two or more groups
called strata
 Subsamples are randomly selected from each
strata

STRATIFIED RANDOM
SAMPLING
Advantages:
 Assures representation of all groups in
sample population
 Characteristics of each stratum can be
estimated and comparisons made
Disadvantages:
 Requires accurate information on proportions
of each stratum
 Stratified lists costly to prepare

CLUSTER SAMPLING
 The population is divided into subgroups (clusters)
like families.
 A simple random sample is taken from each cluster

CLUSTER SAMPLING
Advantages:
 Can estimate characteristics of both cluster
and population
Disadvantages:
 The cost to reach an element to sample is
very high
 Each stage in cluster sampling introduces
sampling error—the more stages there are,
the more error there tends to be

SYSTEMATIC RANDOM
SAMPLING
 Order all units in the sampling frame
 Then every nth number on the list is selected
 N= Sampling Interval

SYSTEMATIC RANDOM
SAMPLING
Advantages:
 Moderate cost; moderate usage
 Simple to draw sample
 Easy to verify
Disadvantages:
 Periodic ordering required

MULTISTAGE SAMPLING
 Carried out in stages
 Using smaller and smaller sampling units at each
stage
1
2
3
4
5
6
7
8
9
10
Primary
Clusters
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
Secondary
Clusters Simple Random Sampling within Secondary Clusters

MULTISTAGE SAMPLING
Advantages:
 More Accurate
 More Effective
Disadvantages:
 Costly
 Each stage in sampling introduces sampling
error—the more stages there are, the more
error there tends to be

 The probability of each case being selected from the
total population is not known.
 Units of the sample are chosen on the basis of
personal judgment or convenience.
 There are NO statistical techniques for measuring
random sampling error in a non-probability sample.
NONPROBABILITY
SAMPLES

 A. Convenience Sampling
 B. Quota Sampling
 C. Judgmental Sampling (Purposive Sampling)
 D. Snowball sampling
 E. Self-selection sampling
NONPROBABILITY SAMPLES

 Convenience sampling involves choosing respondents
at the convenience of the researcher.
Advantages
 Very low cost
 Extensively used/understood
Disadvantages
 Variability and bias cannot be measured or controlled
 Projecting data beyond sample not justified
 Restriction of Generalization.
A. CONVENIENCE SAMPLING

SAMPLING POWERPOINT.pptx popoulation samapling

 The population is first segmented into mutually
exclusive sub-groups, just as in stratified sampling.
Advantages
 Used when research budget is limited
 Very extensively used/understood
 No need for list of population elements
Disadvantages
 Variability and bias cannot be measured/controlled
 Time Consuming
B. QUOTA SAMPLING

 Researcher employs his or her own "expert”
judgment about.
Advantages
 There is a assurance of Quality response
 Meet the specific objective.
Disadvantages
 Bias selection of sample may occur
 Time consuming process.
C. JUDGEMENTAL SAMPLING

 The research starts with a key person and introduce
the next one to become a chain
Advantages
 Low cost
 Useful in specific circumstances & for locating
rare populations
Disadvantages
 Not independent
D. SNOWBALL SAMPLING

 It occurs when you allow each case usually
individuals, to identify their desire to take part in the
research.
Advantages
 More accurate
 Useful in specific circumstances to serve the purpose.
Disadvantages
 More costly due to Advertizing
 Mass are left
E. SELF-SELECTION
SAMPLING

 The errors which arise due to the use of
sampling surveys are known as the sampling
errors.
Two types of sampling errors
 Biased Errors- Due to selection of sampling
techniques; size of the sample.
 Unbiased Errors / Random sampling errors-
Differences between the members of the
population included or not included.
SAMPLING ERRORS

 Specific problem selection.
 Systematic documentation of related research.
 Effective enumeration.
 Effective pre testing.
 Controlling methodological bias.
 Selection of appropriate sampling techniques.
METHODS OF REDUCING
SAMPLING ERRORS

 Non-sampling errors refers to biases and
mistakes in selection of sample.
 CAUSES FOR NON-SAMPLING ERRORS
 Sampling operations
 Inadequate of response
 Misunderstanding the concept
 Lack of knowledge
 Concealment of the truth.
 Loaded questions
 Processing errors
 Sample size
NON-SAMPLING ERRORS

SAMPLING POWERPOINT.pptx popoulation samapling

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