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Secrets to Understanding Cronbach’s Alpha

  • On your research study, reliability is important. In order to determine the consistency of your survey results, use the cronbach’s alpha. In this post, we will be learning about the cronbach’s alpha spss and the secrets on understanding its concept.

    One of the most common methods to measure internal consistency or reliability is the cronbach’s alpha. This is utilized, especially when using multiple Likert questions in a questionnaire and survey, to identify the level of its reliability. On the other hand, we use the Cohen’s (K) kappa to determine the inter-rater reliability.

    To deeply understand the process of cronbach’s alpha spss, below is a sample situation. You can also check  interpretation of anova results spss or manova spss output interpretation if you need.

    cronbach's alpha

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    Cronbach’s Alpha Example

    A study was conducted to determine the safety of people working in an industrial complex through a nine question questionnaires. The questions were devised through a 5-point Likert scale from strongly disagree to strongly agree options. The researcher would like to get a reliable response out of the 15 workers to determine the measure of the respondent’s safety so he uses the Cronbach’s alpha.

    Cronbach’s Alpha SPSS Setup

    In the SPSS Setup, the nine questions were labelled as Qu1 to Qu9. To correctly run the cronbach’s alpha test, it is necessary to enter correctly the data on the SPSS.

    We will thoroughly discussing the process to interpret the cronbach’s alpha results.

    Eight Test Procedures in SPSS

    1. On the top cronbach’s sotware menue, click Analyze> Scale> Reliability Analysis

    2. A dialogue box will pop out that shows the Reliability Analysis from Qu1 to Qu9.

    3. Move the Qu1 to Qu9 variables to the Items box by drag and dropping it through the arrow button.

    4. On the model tab, choose the “Alpha”. The cronbach’s alpha is represented by this. You can also set a scale name by typing it in the Scale label box. But naming this is not necessary so you may leave it blank.

    5. Open the Reliability Analysis: Statistics Box by clicking the Statistics Button.

    6. In the descriptive area, put check on the Item, scale, and scale if item deleted. Check the Correlation option at the Inter-Item area.

    7. You will go back to the Reliability Analysis Dialogue box after clicking the Continue button.

    8. Generate the output by clicking Ok.

    Cronbach’s Alpha Output

    The cronbach’s alpha result provides varieties of tables. One of these tables is the Reliability Statistics, which is imperative in delivering the cronbach’s alpha authentic value.

    Another table that presents the cronbach’s alpha if item deleted is the Item-Total Statistics table. You can find this at the final table column.

    This column shows the cronbach’s alpha value if a particular item was removed from the scale. Removing any of the questions may affect the result.

    A reliable coefficient for a set of variables like questions is provided by cronbach’s alpha spss. Remember that it may not identify different underlying personal qualities like employee commitment and employee motivation. To go through this process, it is important to run first the principal components analysis or PCA.

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