Likert Scale Analysis Calculator

Find the mean, top-2-box and bottom-2-box scores from a 5-point Likert distribution.

Mean across 100 responses

3.15

Top-2-box 40%, bottom-2-box 30%, neutral 30%

How Likert scale analysis works

This calculator summarizes a 5-point Likert response distribution (e.g. Strongly Disagree to Strongly Agree) with the three summary statistics most commonly reported: the mean, top-2-box, and bottom-2-box percentages.

Enter how many respondents chose each of the five scale points. The calculator returns the weighted mean, plus the share who chose the two most positive points (top-2-box) and the two most negative points (bottom-2-box).

Likert data is technically ordinal, not interval — treating it as a mean is a widely used convention in practice, but for rigorous statistical testing, use rank-based methods or the Statistical Test Selector to confirm the right approach for your analysis.

The formula

Mean = Σ(scale point × count) ÷ total responses. Top-2-box = (count₄ + count₅) ÷ total.

Multiply each scale point's value (1 through 5) by its response count, sum those products, and divide by the total number of responses for the mean. Top-2-box and bottom-2-box are simple shares of the total.

Worked example

100 responses: 10, 20, 30, 25, 15 across points 1–5

Mean = (10×1 + 20×2 + 30×3 + 25×4 + 15×5) ÷ 100 = 3.05. Top-2-box = (25 + 15) ÷ 100 = 40%.

Frequently asked questions

Why report top-2-box instead of just the mean?

Top-2-box is easier to communicate to non-technical stakeholders and is less sensitive to how respondents use the middle of the scale than a mean can be.

Can I use this for a 7-point scale?

This version is built for a standard 5-point scale. For a 7-point scale, treat two adjacent points as one bucket, or use the Weighted Average Calculator directly with your own point values.

Is it valid to average Likert data?

It's a common, widely accepted convention for summarizing single items, but Likert data is ordinal. For formal hypothesis testing, the Statistical Test Selector can help you pick a more rigorous rank-based test.

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