Reliability Analysis


Reliability is one of the most important characteristics of any test. It refers to the precision and accuracy of the measurement of the score or data as well as it has the stability of a test measure. In simple words, reliability is the prerequisite for validity as a good measurement instrument is both reliable and valid. The test cannot be valid unless it is reliable, and the reliability ranging from 0 to +1. A reliability coefficient of 0.60 means that 60% of the variance in test scores is due to systematic variance in the characteristic being measured and 40% is due to error variance. Different tests are used to examine the reliability but Cronbach’s alpha is the most famous one among all.  Cronbach’s alpha is used for the determination of reliability of data for this study. Decision criteria for the acceptance or rejection of being reliable are, value > 0.7 suggests reliability and vice versa. The test is run for each variable of study total of eight variables containing three leadership styles and five elements of the climate of the organization individually to observe whether collected data is reliable for analysis.

How to perform Cronbach’s Alpha in SPSS

Step by step procedure for performing Cronbach’s alpha in SPSS.

Click on analyze, then Scale, and then reliability analysis.



Import elements into the right box. I have selected four elements that are used to measure CSR.

 

And Click Ok.


The Results will appear in the Output section of SPSS as follows:


How to interpret Cronbach’s alpha results

The main table that needs to be interpreted is reliability statistics. The results show that 85% of the variance in test scores is due to systematic variance in the characteristic being measured. The data is reliable because the alpha is greater than 0.7.

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