What is Cronbach's alpha?

Cronbach's alpha is a measure of internal consistency or reliability for a set of scale or test items. It tells you how closely related the items are as a group.

What is considered a good Cronbach's alpha?

Rules of thumb: ≥0.9 excellent, 0.8–0.9 good, 0.7–0.8 acceptable, 0.6–0.7 questionable, <0.6 poor. These cutoffs can vary by field.

How do I use this calculator?

Paste your data with respondents in rows and items in columns. Then click Calculate to get alpha, number of items, number of respondents, item variances and item-total correlations.

Cronbach's Alpha Calculator – Internal Consistency & Reliability

Cronbach's Alpha Calculator

Paste your item-level dataset (respondents in rows, items in columns) to compute Cronbach's alpha, number of items, number of respondents, item variances, and item-total correlations. Works for Likert-type scales and test items.

Data (rows = respondents, columns = items)

Accepted separators: comma, semicolon, tab, spaces

Cronbach's α

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Items (k)

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Respondents (n)

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Interpretation

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Item	Mean	Variance	Item-total corr.

Formula

Cronbach's alpha:

\( \alpha = \frac{k}{k-1} \left(1 - \frac{\sum_{i=1}^k \sigma_i^2}{\sigma_T^2} \right) \)

where:

\( k \) = number of items
\( \sigma_i^2 \) = variance of item i
\( \sigma_T^2 \) = variance of total scores (sum of items) across respondents

How to read alpha

≥ 0.90: excellent
0.80 – 0.89: good
0.70 – 0.79: acceptable
0.60 – 0.69: questionable
< 0.60: poor (consider revising items)

Tips

If an item has very low variance or negative item-total correlation, it may lower alpha. Consider removing or revising it and re-running this calculator.