Using scales to measure constructs is widespread in the social sciences and beyond. To support the application of these scales, researchers and practitioners need to show evidence of appropriate reliability and validity. Many different types of reliability exist, but internal consistency reliability is perhaps the most popular. Even yet, many metrics exist to provide evidence of internal consistency reliability, but Cronbach’s alpha is perhaps the most popular of these. For this reason, I provide a guide below of how to calculate Cronbach’s alpha in SPSS. If you have any questions or comments after reading, please contact me at MHoward@SouthAlabama.edu.

Typically, I begin my guides with a brief review of the statistic; however, one of my prior DBA students, Chad Marshall, wrote a fantastic introduction to Cronbach’s alpha which was previously featured on MattCHoward.com. If you need to learn more about Cronbach’s alpha, click here to read it.

Once you are familiar with Cronbach’s alpha, we can then use SPSS to calculate it. If you don’t have a dataset, you can download the example dataset here. In the dataset, we are investigating the relationship of job satisfaction and job performance, but we need to see whether our job satisfaction measure is internally consistent first.

The data should look something like this:

If your dataset looks differently, you should try to reformat it to resemble the picture above. The instructions below may be a little confusing if your data looks a little different.

Once you have the data open, the first step is to click on the Analyze tab at the top.

Then click on Scale.

Then click on Reliability Analysis.

Now, a window like this should pop up:

You’ll want to click on each variable that you’re interested in, then click on the arrow to put the variables in the other window. You can do this one at a time, or you can highlight them all at once then click on the arrow.

Your final window should look like the following, and then you should push OK.

We got results! The table below is very straightforward. The first tells us that we had 30 participants with 0 excluded. The second tells us that our scale included 4 items with a Cronbach’s alpha of .86. As we know from reading our guide on Cronbach’s alpha, this result suggests that our scale demonstrates appropriate levels of internal consistency. Yay!

Using the same dataset, you can also calculate the Cronbach’s alpha of the job performance scale using the same method. It’s Cronbach’s alpha should be .755. Hopefully from this practice, you should now be able to calculate a Cronbach’s alpha on your own. Good work! As always, if you have any questions or comments, please email me at MHoward@SouthAlabama.edu.