Cronbach's alpha calculator
Paste your item-by-respondent scores and check whether a scale holds together before you trust it in your analysis.
Cronbach's alpha measures the internal consistency of a multi-item scale: the degree to which the items move together and appear to measure the same underlying construct. It ranges up to 1, with .70 the usual floor for an acceptable scale and .80 or above preferred. This calculator returns alpha along with the per-item statistics, the corrected item-total correlation and the alpha if an item were deleted, so you can see which items carry the scale and which weaken it.
Cronbach's alpha
0.958
Excellent internal consistency. Based on 8 respondents and 5 items.
Item statistics
| Item | Mean | Variance | Item-total r | Alpha if deleted |
|---|---|---|---|---|
| Item 1 | 3.38 | 1.98 | 0.974 | 0.931 |
| Item 2 | 3.13 | 1.27 | 0.841 | 0.955 |
| Item 3 | 3.38 | 1.70 | 0.842 | 0.954 |
| Item 4 | 3.50 | 2.29 | 0.938 | 0.940 |
| Item 5 | 3.63 | 1.13 | 0.858 | 0.954 |
An “alpha if deleted” that is higher than the overall alpha flags an item that may be weakening the scale. A low item-total correlation points the same way.
How alpha is calculated
For a scale of k items, alpha compares the sum of the individual item variances with the variance of the total score:
α = (k / (k - 1)) × (1 - Σs²item / s²total)
When the items are highly correlated, the total-score variance is large relative to the summed item variances, and alpha approaches 1. All variances use the sample (n - 1) denominator, matching the SPSS reliability procedure, so the figure here agrees with what SPSS reports.
The corrected item-total correlation correlates each item with the sum of the other items, and the alpha if deleted column recomputes alpha with each item removed in turn. A higher alpha-if-deleted than the overall figure is the clearest signal that an item does not belong with the rest.
The guides behind this tool
Frequently asked questions
- How do you calculate Cronbach's alpha in SPSS?
In SPSS, choose Analyze, then Scale, then Reliability Analysis, move your item variables into the box, and select the Alpha model. The output gives the alpha coefficient and, under the statistics options, the alpha-if-item-deleted column. This calculator returns the same coefficient and item table directly from a pasted grid, with no software to install.
- Can you calculate Cronbach's alpha in Excel?
Yes, but it is laborious: you compute the variance of each item and of the total score, then apply the alpha formula by hand or with a custom worksheet, because Excel has no built-in alpha function. That manual route is where mistakes creep in. Pasting your data into this calculator gives the same result instantly, along with the item-total correlations.
- What is too high for Cronbach's alpha?
An alpha above about 0.95 is often treated as too high, because it suggests the items are redundant and may be asking the same question in slightly different words. Very high values can mean the scale is longer than it needs to be rather than that it is exceptionally reliable. The item table above flags items whose removal barely changes alpha.
- Why do you calculate Cronbach's alpha?
Cronbach's alpha estimates internal consistency, the degree to which the items on a scale measure the same underlying construct. Researchers report it to show that a questionnaire or subscale hangs together before they use its total score in further analysis. The coefficient ranges from 0 to 1, with higher values indicating items that correlate more strongly with one another.