Upload your survey data, pick the items that should measure the same thing, and get Cronbach's alpha with a confidence interval, a full item analysis, and the one item to cut if your scale is weak. Free.
Free analyses run on up to 10,000 rows. Larger files are randomly sampled to that size — sign up to analyze your full dataset.
Computing scale reliability...
Sent to — Cronbach's alpha with interpretation band and confidence interval, item-total correlations, alpha-if-deleted, the inter-item correlation summary, R code, and AI insights.
Analyze another fileThe analysis takes your scale items, keeps the responses with no missing item, and computes Cronbach's alpha — the ratio of shared, systematic variance to total variance across the items. It reports the interpretation band (unacceptable through excellent), a Feldt confidence interval, and the standardized alpha derived from the mean inter-item correlation. For each item it computes the corrected item-total correlation (how well that item tracks the sum of the others) and the alpha the scale would have without it, so weak or redundant items are obvious. An inter-item correlation summary shows the mean and range of how the items relate.
Use it whenever you plan to average or sum several questions into one score — attitude scales, satisfaction indices, personality subscales, test forms — and need to know the items actually belong together.
Not for a single item, not for categorical or nominal responses, and not a substitute for a factor analysis when you suspect the items measure more than one thing.
Built for: Researchers, survey designers, psychometricians, and analysts building composite scores
Typical data source: A wide-format spreadsheet with one column per survey or test item and one row per respondent
Wide format — one column per item, one row per respondent. For example, five job-satisfaction questions answered on a 1-7 agreement scale:
Minimum 10 rows · Best with 50-5,000 respondents and 3-20 items
Standard-library analysis: are a set of survey or test items consistent enough to be summed into a single scale? Map three or more Likert or scale items and get Cronbach's alpha with its interpretation band and a 95% confidence interval, the standardized alpha from the mean inter-item correlation, a full item analysis (each item's mean, spread, corrected item-total correlation, and the alpha you would get if that item were removed), and the inter-item correlation summary. Built for survey validation: it tells you whether your scale holds together and which item to cut if it does not.
Each item's mean, spread, how well it tracks the rest of the scale (corrected item-total correlation), and the alpha you would get by dropping it — weak items are flagged.
The reliability the scale would have with each item removed; bars above the overall-alpha line mark items that are hurting the scale.
The raw and standardized alpha, the mean and range of inter-item correlations, and the confidence interval — the components behind the headline number.
Plain-English interpretation — what the numbers mean, what's significant, and what to do next.
Can I sum these survey items into one score?
Map your Likert items. You get Cronbach's alpha with an interpretation band and confidence interval, plus an item analysis that flags any question that does not track the others and shows exactly how much reliability you would gain by dropping it.
See our FAQ for details on pricing, data privacy, and how the analysis works. Every report includes a Methodology section showing the statistical test, assumptions checked, and diagnostics run.
Run any analysis on your own data — validated R analyses, interactive reports, AI insights, and PDF export.
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