Reliability test in SPSS using Cronbach Alpha

By Priya Chetty & Shruti Datt on February 7, 2015

Cronbach Alpha is a reliability test conducted within SPSS in order to measure the internal consistency i.e. reliability of the measuring instrument (Questionnaire). It is most commonly used when the questionnaire is developed using multiple Likert scale statements and therefore to determine if the scale is reliable or not.


A researcher developed a 9-question questionnaire to determine how safe people feel at their work. In addition, the questions were on the 5-point Likert Scale with responses ranging from “Strongly agree” to “Strongly disagree”. In order to determine if the questionnaire could “reliably” measure the latent variable i.e. feeling of safety, the Cronbach alpha test was conducted. The acceptable reliability value is 0.6.

Cronbach Alpha in SPSS

  • Step 1: On the Menu, Click Analyze -> Scale -> Reliability Analysis (Figure 1).
Figure 1: Cronbach Alpha in SPSS
Figure 1: Cronbach Alpha in SPSS
  • Step 2: Next the Reliability Dialog box would open which is shown below. All the questions which are to be checked for Reliability are transferred to the “Items box” (Figure 2)
Figure 2: Cronbach Alpha in SPSS
Figure 2: Cronbach Alpha in SPSS
  • Step 3: Next Click on “Statistics” which leads to another dialogue box. Here under “Descriptives for” check Item, Scale, and Scale if Item Deleted. In Inter-Item Check Correlations. Click “Continue” and then “OK” to Run the test (Figure 3).
Figure 3: Cronbach Alpha in SPSS
Figure 3: Cronbach Alpha in SPSS
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Output and results

Table 1 given below is the Reliability Statistics Table which provides the value for Cronbach alpha which in this case is .805 and reflects the high reliability of the measuring instrument. Furthermore, it indicates a high level of internal consistency with respect to the specific sample.


Table 2 “Item Total Statistics” presents the results for Cronbach Alpha if the Item is deleted. It is the measure of Reliability to determine the “Item”, when deleted would enhance the overall reliability of the measuring instrument.

Table 2: Item Total Statistics
Table 2: Item Total Statistics

In above table 2, the item-total statistics depict the statement-wise efficiency of a construct. It is essential to know whether all statements are effectively measuring a factor. Therefore, item-wise statistics are measured. The above table shows that the lowest corrected statistics are for Qu8 which is 0.128 which might have been contributing to reducing the overall reliability. The Cronbach alpha value if the item deleted score of 0.823 further proves this.


The general rule is that if any statement that has a Cronbach alpha value if item deleted more than the existing total Cronbach alpha value, then it should be eliminated. Thus, this is an effective way of improving Cronbach’s alpha value of reliability.


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