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Sampling and Selection
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Sampling - a process used in statistical analysis in which a predetermined number of observations will be taken from a larger population.
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TARGET POPULATION
STUDY POPULATION
SAMPLE
SAMPLING…….
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Selection - the action or fact of carefully choosing someone or something as being the best or most suitable.
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Whatever your approaches are, one should give
consideration to the related issues of sampling and
selection.
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SAMPLING BREAKDOWN
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PROBABILITY SAMPLING¤Simple Random Sampling
¤Systematic Sampling¤Stratified Sampling¤Cluster Sampling¤Stage Sampling
SAMPLING STRATEGIES
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Simple Random Sampling
Selection at
random
Probability Sampling
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Systematic Sampling
Selecting every
nth case
Probability Sampling
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Systematic SamplingEvery nth member ( for example: every 10th person) is selected from a list of all population members.
Probability Sampling
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Stratified Sampling
Sampling within
groups of the
population
Probability Sampling
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Stratified SamplingThe population is divided into two or more groups called strata, according to some criterion, such as geographic location, grade level, age, or income, and subsamples are randomly selected from each strata.
Probability Sampling
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Cluster Sampling Surveying whole
clusters of the
population sampled at
random
Probability Sampling
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Cluster SamplingThe population is divided into subgroups (clusters) like families. A simple random sample is taken of the subgroups and then all members of the cluster selected are surveyed.
Probability Sampling
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Stage Sampling
Sampling clusters
sampled at random
Probability Sampling
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Both systematic and stratified sampling are
more complex approaches while cluster and stage
sampling are more focused
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The most widely understood probability sampling approach is probably
random sampling, where every individual or object
in the population of interest has an equal
chance of being chosen for study
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NON-PROBABILITY SAMPLING¤Convenience Sampling¤Voluntary Sampling¤Quota Sampling¤Purposive Sampling¤Dimensional Sampling¤ Snowball Sampling
SAMPLING STRATEGIES
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Convenience Sampling
Sampling those most convenient
Non-Probability Sampling
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Convenience Sampling Selection of whichever individuals are
easiest to reach It is done at the “convenience” of the
researcher
Non-Probability Sampling
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Voluntary Sampling
Sample is self-selected
Non-Probability Sampling
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Quota Sampling
Convenience sampling within groups of the
population
Non-Probability Sampling
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Purposive Sampling
Handpicking supposedly typical or
interesting cases
Non-Probability Sampling
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Dimensional Sampling
Multidimensional quota sampling
Non-Probability Sampling
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Snowball Sampling
Building up a
sample through
informants
Non-Probability Sampling
26Non-probability sampling approaches are used
when the researcher lacks a sampling frame for the population in question or
where probabilistic approach is not judged to
be necessary.
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Other Kinds of Sampling
Event Sampling : using routine or special events as the basis for sampling.
Time sampling: recognizing that different parts of the day, week or year may be significant.
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4 Main Techniques/ Methods for producing data
1. Documents2. Interviews3. Observation4. Questionnaires
Applying Techniques To Data Collection
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Documents
All research projects involve, to a greater or lesser extent, the use and analysis of
documents.
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“In paying due attention to such materials, however, one must be quite
clear about what they can and cannot be used for. Documents are 'social facts', in that they are produced, shared and used in socially organized ways. They are not, however, transparent representations of organizational routines, decision-making
processes, or professional diagnoses. They construct particular kinds of representations using their own
conventions.”Atkinson, P. and Coffey, A. (2004). Analysing documentary
realities. In D. Silverman (Ed.), Qualitative research, London: Sage: 45-62.
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Researchers are expected to :¤ Read¤ Understand ¤ Analyze criticallyThe writings of the others, whether fellow researchers, practitioners or policy-makers. Considerable
attention.
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The focus of data collection is wholly, or almost entirely, on documents of various kinds.
be library-based, be computer-based, have a policy focus, have a historical orientation
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aimed at producing a critical synopsis of an existing area
of research writing;
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consisting largely of the analysis of
previously collected data sets;
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examining materials relevant to a
particular set of policy decisions;
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making use of available archival and
other surviving documentary
evidence.
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The questions you need to ask of any existing Document
What were the conditions of its production?
If you are using statistical data sets, have the variables changed over time?
If you are using statistical data sets, have the indicators used to measure variables changed?
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Reasons for Using Secondary Data
1. Because collecting primary data is difficult, time consuming and expensive.
2. Because you can never have enough data.
3. Because it makes sense to use them if the data you want already exist in some form.
39Reasons for Using Secondary Data
4. Because they may shed light on, or complement, the primary data you have collected.
5. Because they may confirm, modify or contradict your findings.
6. Because they allow you to focus your attention on analysis and interpretation.
40Reasons for Using Secondary Data
7. Because you cannot conduct a research study in isolation from what has already been done.
8. Because more data are collected than are ever used.
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