Reliability in SPSS - Coefficient alpha (Part 1)

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Learn how to calculate and interpret a reliability coefficient in SPSS using Coefficient (Cronbach's) alpha (Part 1)

Coefficient alpha
Cronbach's alpha
internal consistency reliability

How to Calculate and Interpret Coefficient Alpha (Cronbach's alpha) in SPSS is shown in this video

Cronbach's Alpha
Coefficient Alpha
Internal Consistency
Reliability

In this video, we'll take a look at Coefficient alpha, and how to run that in SPSS. Coefficient alpha is one way to estimate the reliability of an instrument (internal consistency reliability). In this example, we'll look at the satisfaction with life scale (Diner et al, 1985), which consists of 5 items on a 7-point Likert scale. You are probably familiar with Likert scales and have taken them before. With 5 questions on a 1 to 7 scale, the lowest possible total score is 5 to a high possible score of 35 (answering 7 on every question). Any total score outside of this range (5 to 35) would indicate that an error had been made.

In SPSS, there are 5 different variables with responses for 80 total people. To run the analysis, we want to select Analyze, then Scale, followed by Reliability Analysis. Move all 5 variables (items) to the item box. We'll add the label "Satisfaction with Life Scale." Next, click Statistics and select all the values under Descriptives for section of the table. Click Continue, then OK.

Our second table of output, Reliability Statistics, contains the value we are most interested in, Cronbach's Alpha. Our reliability estimate is .88, which is very good. (See part 2 for further discussion of the output.)

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