Sampling and Selection in research

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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


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Systematic SamplingEvery nth member ( for example: every 10th person) is selected from a list of all population members.


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Stratified Sampling

Sampling within

groups of the

population


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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.


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Cluster Sampling Surveying whole

clusters of the

population sampled at

random


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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.


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Stage Sampling

Sampling clusters

sampled at random


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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


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Voluntary Sampling

Sample is self-selected


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Quota Sampling

Convenience sampling within groups of the

population


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Purposive Sampling

Handpicking supposedly typical or

interesting cases


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Dimensional Sampling

Multidimensional quota sampling


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Snowball Sampling

Building up a

sample through

informants


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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