Calculator
Choose a mode, enter values, then calculate. Use Add row for longer scales.
Formula used
This calculator uses a weighted mean. Each row is a score value with a frequency and an optional weight.
The confidence interval is computed using a normal approximation: x̄ ± z × SE, where SE = SD / √N and N = Σ(wᵢ).
How to use this calculator
- Select Frequency table or Raw responses.
- Enter your scores and counts, or paste responses.
- Optional: add weights, decimals, and confidence level.
- Press Calculate mean score to see results.
- Use Download CSV or Download PDF for reports.
Example data table
Example Likert scale. Mean equals Σ(score × frequency) ÷ Σ(frequency).
| Response | Score | Frequency | Score × Frequency |
|---|---|---|---|
| Strongly Disagree | 1 | 2 | 2 |
| Disagree | 2 | 4 | 8 |
| Neutral | 3 | 6 | 18 |
| Agree | 4 | 5 | 20 |
| Strongly Agree | 5 | 3 | 15 |
| Totals | 20 | 63 | |
Why survey mean scores are useful
Mean scores compress many responses into one comparable value. On a 1–5 scale, 3.00 often signals neutrality, while 4.00 suggests strong agreement. When you track items over time, a shift from 3.15 to 3.60 is a 14.3% improvement relative to the 1–5 range. Mean scores are most informative when the scale is consistent and responses are collected under similar conditions.
Selecting the right scale and coding
Common survey designs use 1–5 or 1–7 choices. Keep the direction consistent: higher should always mean “more” of the trait. If you reverse-code a negative statement, convert it before calculating. For a 1–5 scale, reverse coding is new = 6 − old. Clear coding prevents artificial mean inflation or deflation.
Working with frequencies and weights
Frequency tables are efficient for Likert summaries. The calculator multiplies score × frequency × weight, then divides by total effective weight. Weights are helpful when combining items with different importance, such as giving “Service Quality” weight 1.5 and “Packaging” weight 1.0. If you do not need weighting, keep every weight as 1 to match a standard mean.
Understanding spread, error, and confidence
A mean without spread can mislead. Standard deviation indicates how clustered responses are; low SD means stronger consensus. Standard error shrinks as sample size grows, roughly by 1/√N. With N = 100, SE is about one-third of the SE at N = 10. The confidence interval uses mean ± z × SE to show a plausible range for the population mean.
Reporting results clearly
For dashboards, report the mean with N and a confidence interval, such as 3.42 (N=250, 95% CI 3.35–3.49). Add median and mode when results are skewed. Include the underlying frequency table in appendices so reviewers can see response distribution. Exports to CSV and PDF help preserve the calculation trail for audits and stakeholder updates.
When comparing groups, calculate means separately for each segment, such as region or age band. A gap of 0.30 on a 1–5 scale is meaningful in UX surveys. Always note handling of missing responses and exclude zeros unless they are valid.
FAQs
What is a survey mean score?
It is the average of numeric response values. In frequency mode, it is a weighted mean computed from scores, counts, and optional weights. It helps compare items and track change across survey waves.
When should I use weights?
Use weights when some categories or questions should influence the mean more than others, or when correcting for sampling imbalance. If every response should count equally, keep weights at 1.
How are missing or invalid values handled?
In raw mode, non-numeric entries are ignored. In frequency mode, rows with missing score or frequency, or non-positive frequency, are skipped. Only include zeros if they represent a valid score in your scale.
What confidence level should I choose?
95% is a common default for reporting. Use 90% for quicker directional checks and 99% for stricter evidence. The interval here uses a normal approximation, so very small samples may need a t-based approach.
Can I paste raw responses from a spreadsheet?
Yes. Paste values separated by commas, spaces, or new lines. The calculator extracts numbers and builds summary statistics automatically. For Likert summaries, frequency mode is usually faster and easier to audit.
What should I include in a report?
Report the mean, sample size, and confidence interval, plus the scale definition. Add a frequency table or chart for transparency. If weights were used, state why and how they were applied.