Definition
The Likert scale is a psychometric scale commonly used in questionnaires to measure respondents’ attitudes or feelings towards a subject. Named after psychologist Rensis Likert, who developed the technique in 1932, it provides a range of fixed response options from one extreme attitude to another. Typically, a Likert scale is made up of 5 or 7 points, with the midpoint representing neutrality.
Components of the Likert Scale
- Response Points: Likert scales commonly include 5 or 7 points, with each point corresponding to a respondent’s level of agreement or disagreement. The most typical form includes the following options: strongly disagree, disagree, neither agree nor disagree, agree, and strongly agree.
- Symmetry: The scale is usually balanced to allow for a symmetrical range of responses from positive to negative.
- Labels: Each point on the scale is labeled to represent the intensity of feeling about the statement being assessed.
Importance in Research and Survey Design
The Likert scale is extensively used in survey research to measure psychological attitudes. It is favored for its simplicity and effectiveness in capturing the intensity of feelings towards a given statement. By quantifying qualitative data, it allows for the data to be analyzed statistically.
Applications
- Customer Satisfaction: Assessing how customers feel about product quality, service interaction, or overall satisfaction.
- Employee Engagement: Measuring employees’ attitudes towards their work environment, management, and job roles.
- Academic Research: Gathering data on people’s attitudes or behaviors in social sciences.
Benefits
- Ease of Use: The Likert scale is straightforward for respondents to understand and for researchers to analyze.
- Versatility: It can be used in a variety of fields and for a broad range of topics.
- Sensitivity: The scale can detect variations in attitudes or feelings that might be missed by a simple yes/no question.
Challenges
- Central Tendency Bias: Respondents may avoid extreme responses and tend towards middle options, potentially skewing data.
- Interpretation of Scales: Different respondents may interpret the meaning of scale points differently, affecting the reliability of the data.
- Over-simplification: Reducing complex opinions to a simple scale might not capture the full spectrum of a respondent’s attitudes.
Statistical Analysis
In analyzing data from Likert scales, median and mode are generally more meaningful than the mean, as the data are ordinal. Advanced statistical techniques such as factor analysis might also be used to examine the data dimensions represented in a set of Likert items.
The Likert scale remains a valuable tool in both academic research and practical applications like market research, due to its ability to efficiently gather and analyze opinions and attitudes. Its continued relevance in various fields underscores its utility in translating complex qualitative responses into quantifiable data, facilitating easier analysis and interpretation.
Related
Customer Satisfaction Score (CSAT)
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