Statistical Assumption
- Farah Faisal
- May 11, 2018
- 1 min read
The next stage of data analysis is testing Statistical Assumption.
Every statistical analysis has a set of assumptions that need to be met before using the data. One of the these assumptions is that data is normally distributed.
In SPSS, there is a way to find out the normality of data by going to Analyze --> Descriptive Statistics --> Explore. The variables that need to be checked are then chosen in Dependent List.
The following images show the normality tests for both total scores under both scales.
DASS-21 - Time 1 & 2








A Shapiro-Wilk test was used to test for normality on Total DASS scores before and after positivity treatment. The Sig. values for Total DASS scores before treatment (p = 0.399) and after treatment (p = 0.62) indicate a non-significant result, therefore normality is assumed on both scores.
Self Esteem - Time 1 & 2








Another Shapiro-Wilk test was used to test for normality on Total SE scores before and after positivity treatment. The Sig. value for Total SE score before treatment (p = 0.013) indicate a statistically non-significant result, therefore assumption of normality has been met. However, the Sig. value for Total SE score after treatment (p = 0.001) indicate a statistically significant result, therefore violating the assumption of normality.
The next step after assessing normality is to conduct Descriptive Statistics, which will be covered in the next post.
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