Checking normality using skewness, kurtosis, Kolmogorov–Smirnov and Shapiro-Wilk tests

In this video, I will explain how to use SPSS to evaluate check for normality using skewness, kurtosis, Kolmogorov–Smirnov and Shapiro-Wilk tests.

Please also check the following video for further information:
   • Normality, Skewness, Kurtosis, & Shap...  

The criteria that I will explain are as follows:
1. Skewness & Kurtosis
Samples below 50: use the z value. -1.96 and +1.96 (Z scores for kurtosis and skewness are computed by dividing the skewness and kurtosis by their SE)
Samples between 50 and 300: use a more liberal z range. -3.29 and +3.29
Larger samples:
Absolute skewness value between -2 and +2.
Absolute kurtosis value between -7 and +7
2. Kolmogorov–Smirnov test AND Shapiro-Wilk test
Use with samples below 300
For samples larger than 300, they may be unreliable.

Data used in this video were derived from Core 3 Research Programme: A Quantitative Study of Learning and Teaching in Singapore Classrooms, the property of the National Institute of Education, Nanyang Technological University, Singapore.