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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.