Reliability Analysis (Cronbach's Alpha) in SPSS

Reliability Analysis in SPSS

Cronbach's Alpha is the most widely used measure of internal consistency reliability. It tells you how closely related a set of items are as a group.

Step-by-Step: Calculating Cronbach's Alpha

Step 1: Open Your Data File

Make sure your data is entered correctly with all Likert scale items.

Step 2: Navigate to Reliability Analysis

Analyze → Scale → Reliability Analysis

Step 3: Select Items

• Move the items of one dimension to the "Items" box
• Keep Model as "Alpha"

Step 4: Click Statistics

Check the following options:

• ✅ Item (under Descriptives for)
• ✅ Scale (under Descriptives for)
• ✅ Scale if item deleted
• ✅ Correlations (Inter-Item)

Step 5: Click OK and Read Results

Understanding the Output

1. Reliability Statistics Table

Alpha = 0.847 → Good reliability ✓

2. Item-Total Statistics Table

The key column is "Cronbach's Alpha if Item Deleted":

Decision Rules:

• If "Alpha if Item Deleted" is higher than the overall Alpha → consider removing that item
• If "Corrected Item-Total Correlation" is below 0.30 → the item is weak

In the example above, Q3 has a low correlation (0.234) and deleting it would improve Alpha from .847 to .876. Consider removing or revising Q3.

Performing Reliability for Each Dimension

Repeat the process for each dimension separately, then for all items together:

1. Dimension 1 items → Calculate Alpha
2. Dimension 2 items → Calculate Alpha
3. Dimension 3 items → Calculate Alpha
4. All items together → Calculate overall Alpha

Reporting in Your Research

Create a summary table:

Note: Always report reliability results in your methodology chapter. Reviewers and supervisors will look for this as evidence of instrument quality.