Page 103 - DLIS401_METHODOLOGY_OF_RESEARCH_AND_STATISTICAL_TECHNIQUES

Methodology of Research and Statistical Techniques

Notes 4. ........................ is a common nonprobability method.

(a) Quota sampling (b) Stratified sampling
(c) Convenience sampling (d) Judgment sampling.
5. ........................ is the nonprobability equivalent of stratified sampling.
(a) Judgment sampling (b) Quota sampling

(c) Random sampling (d) Systematic sampling.

6.4 Precision and Accuracy of Sample Based Research

The best sampling method is the method that most effectively meets the particular goals of the
study in question. The effectiveness of a sampling method depends on many factors. Because
these factors interact in complex ways, the “best” sampling method is seldom obvious. Good
researchers use the following strategy to identify the best sampling method.
• List the research goals (usually some combination of accuracy, precision, and/or cost).
• Identify potential sampling methods that might effectively achieve those goals.

• Test the ability of each method to achieve each goal.
• Choose the method that does the best job of achieving the goals.
It is important to distinguish from the start a different between accuracy and precision:—

(1) Accuracy is the degree to which information in a digital database matches true or accepted
values. Accuracy is an issue pertaining to the quality of data and the number of errors contained
in a dataset or map.
• The level of accuracy required for particular applications varies greatly.
• Highly accurate data can be very difficult and costly to produce and compile.

(2) Precise attribute information may specify the characteristics of features in great detail. It
is important to realize, however, that precise data—no matter how carefully measured—may
be inaccurate. Surveyors may make mistakes or data may be entered into the database incorrectly.
• The level of precision required for particular applications varies greatly. Engineering
projects such as road and utility construction require very precise information measured
to the millimeter or tenth of an inch. Demographic analyses of marketing or electoral
trends can often make do with less, say to the closest zip code or precinct boundary.
• Highly precise data can be very difficult and costly to collect.

High precision does not indicate high accuracy nor does high accuracy imply high precision.
But high accuracy and high precision are both expensive.
Two additional terms are used as well:

1. Data quality refers to the relative accuracy and precision of a particular database. These
facts are often documented in data quality reports.
2. Error encompasses both the imprecision of data and its inaccuracies.

6.4.1 Quality of Survey Results

When researchers describe the quality of survey results, they may use one or more of the
following terms.

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