Research Methodology
The gold standard for evaluating the internal consistency of survey items.
Cronbach’s Alpha determines if a set of survey items aims to measure the same construct. It answers the critical question:
“Do all items in my scale reliably measure the same underlying concept?”
$$ \alpha = \frac{N \times \bar{c}}{\bar{v} + (N - 1) \times \bar{c}} $$
The number of items in your scale.
Average inter-item covariance (how items vary together).
Average variance of the items.
Research-quality instruments should generally aim for α ≥ 0.70.
| Cronbach’s Alpha (α) | Reliability Level |
|---|---|
| ≥ 0.90 | Excellent |
| 0.80 – 0.89 | Good |
| 0.70 – 0.79 | Acceptable (Min.) |
| 0.60 – 0.69 | Questionable |
| < 0.60 | Poor |
Enter your Alpha value below to see the interpretation instantly.
Use for surveys with multiple items measuring the same construct.
Essential during the pilot phase to refine your questionnaire.
Run before Exploratory Factor Analysis (EFA) to ensure item cohesion.
Delete items with low "Item-total correlations" shown in SPSS.
Avoid double-barreled or confusingly worded questions.
Use 3–5 items per construct for optimal consistency.
Analyze Scale Reliability Analysis
Move your relevant survey items into the Items box.
Click Statistics and tick the box for "Scale if item deleted". This is crucial for optimization!
Click OK and analyze the output table.