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Cronbach’s Alpha is a statistical measure used to assess the internal consistency or reliability of a set of items or questions in a survey or test. It can be calculated in SPSS by running a reliability analysis, which can be found under the “Analyze” tab. A window will appear where the user can select the items to be included in the analysis. Once the analysis is run, the results will include the Cronbach’s Alpha coefficient, which ranges from 0 to 1. For example, if a researcher wants to measure the internal consistency of a 10-item questionnaire on job satisfaction, they can use Cronbach’s Alpha in SPSS to determine the reliability of the questionnaire. A coefficient of 0.8 or higher is generally considered to indicate good reliability.
Chronbach’s Alpha is a way to measure the of a questionnaire or survey.
Cronbach’s Alpha ranges between 0 and 1, with higher values indicating that the survey or questionnaire is more reliable.
The easiest way to calculate Cronbach’s Alpha in SPSS is to use Analyze > Scale > Reliability Analysis.
The following example shows how to do so in practice.
Example: How to Calculate Cronbach’s Alpha in SPSS
Suppose a restaurant manager wants to measure overall satisfaction among customers.
She decides to send out a survey to 10 customers who can rate the restaurant on a scale of 1 to 3 for various categories.
The following dataset shows the ratings that each of the customers gave to the 3 questions on the survey:
To calculate Cronbach’s Alpha for the survey responses, click the Analyze tab, then click Scale, then click Reliability Analysis:
In the new window that appears, drag Q1, Q2 and Q3 into the Items panel.
Leave Alpha selected in the Model dropdown to indicate that you’d like to calculate Cronbach’s Alpha.
Next, click the Statistics button in the top right corner and then check the boxes under Descriptives for Item, Scale and Scale if item deleted:
Then click Continue. Then click OK.
From the output we can see that Cronbach’s Alpha is 0.773.
The Item Statistics and Item-Total Statistics show various descriptive statistics for each individual question on the survey along with the value of Cronbach’s Alpha if individual items were deleted from the survey.
The following table describes how to interpret different values of Cronbach’s Alpha:
| Cronbach’s Alpha | Internal consistency |
|---|---|
| 0.9 ≤ α | Excellent |
| 0.8 ≤ α < 0.9 | Good |
| 0.7 ≤ α < 0.8 | Acceptable |
| 0.6 ≤ α < 0.7 | Questionable |
| 0.5 ≤ α < 0.6 | Poor |
| α < 0.5 | Unacceptable |
Since we calculated Cronbach’s Alpha to be 0.773, we would say that the internal consistency of this survey is “Acceptable.”
Bonus: Feel free to use this to find Cronbach’s Alpha for a given dataset.