Likert Scale
A psychometric scale commonly used in surveys that asks respondents to rate their level of agreement with a statement, typically on a 5- or 7-point scale.
The Likert scale, developed by Rensis Likert in 1932, is one of the most widely used rating scales in survey research. It asks respondents to indicate their level of agreement or satisfaction along a symmetric scale, such as "Strongly Disagree, Disagree, Neutral, Agree, Strongly Agree."
Likert scales can be 5-point, 7-point, or even 10-point. Five-point scales are simpler and reduce cognitive load. Seven-point scales offer more granularity and may capture subtler differences in opinion. The choice depends on the context and the level of precision needed.
A key design consideration is whether to include a midpoint (neutral option). Including it allows respondents who genuinely have no opinion to express that, but it can also attract respondents who are simply avoiding a decision. Some researchers remove the midpoint to force a directional response.
When analyzing Likert scale data, treat the responses as ordinal (ranked) rather than interval (equally spaced). While it is common practice to calculate means from Likert data, strictly speaking, the distance between "Agree" and "Strongly Agree" may not be the same as between "Neutral" and "Agree." Top-box analysis (percentage selecting the top one or two options) is a statistically safer approach.
Related Terms
Survey Design
MethodologyThe practice of crafting survey questions, structure, and flow to maximize response quality, minimize bias, and generate actionable insights.
Customer Satisfaction Score (CSAT)
MetricsA metric that measures how satisfied customers are with a product, service, or interaction, typically on a 1–5 scale.
Customer Effort Score (CES)
MetricsA metric that measures how much effort a customer had to exert to get an issue resolved, a request fulfilled, or a task completed.
Response Bias
MethodologyA systematic tendency for survey respondents to answer inaccurately or untruthfully, skewing results away from the true population sentiment.
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