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ANALYZING LIKERT DATA
ORIGIN
Named after its inventor, the US organizational-behavior psychologist Dr. Rensis
Likert (1903-81), Likert Scale is a method of ascribing quantitative value to qualitative
data, to make it amenable to statistical analysis. A numerical value is assigned to each
potential choice and a mean figure for all the responses is computed at the end of the
evaluation or survey.
It is used mainly in training course evaluations and market surveys. Likert scales
usually have five potential choices (strongly agree, agree, neutral, disagree, strongly
disagree) but sometimes go up to ten or more. The final average score represents overall
level of accomplishment or attitude toward the subject matter.
In all likelihood, you have used a Likert scale (or something you have called a Likert
scale) in a survey before.
It might surprise you to learn that Likert scales are a very specific type of survey
question, and what you have been calling “Likert” may be something entirely different.
Not to worry — researchers that have been doing surveys for years still get their
definitions confused. In fact, many researchers don’t even agree on the best way to report
on the numeric values in a Likert scale.
To try and clear up any confusion, we’ll take a look at the traditional and, in our
opinion, most valuable way to use Likert scales and report on them.
WHAT IS A LIKERT SCALE?
It is a psychometric scale commonly involved in research that employs questionnaires.
It is the most widely used approach to scaling responses in survey research.
Likert scales are a non-comparative scaling technique and are one-dimensional in
nature.
When responding to a Likert questionnaire item respondents specify their level of
agreement or disagreement on a symmetric agree-disagree scale for a series of
statements.
