Normality Tests for Statistical Analysis: A Guide for Non-Statisticians
By Asghar Ghasemi, S. Zahediasl. International Journal of Endocrinology and Metabolism, 2012
1,635 citations recorded by the source corpus.
Statistical errors are common in scientific literature and about 50% of the published articles have at least one error. The assumption of normality needs to be checked for many statistical procedures, namely parametric tests, because their validity depends on it. The aim of this commentary is to overview checking for normality in statistical analysis using SPSS.
Subfields: Cardiology and Cardiovascular Medicine, Public Health, Environmental and Occupational Health
View Paper: https://www.semanticscholar.org/paper/cf7137406053394fd685de93857ccf52a04f449b
Citations in the corpus
- Violating the normality assumption may be the lesser of two evils (2018, neutral): “Formal tests for normality have been criticized because they have low power at small sample sizes and almost always yield significant deviations from normality at large sample sizes (Ghasemi & Zahediasl 2012).”
- Validity and Reliability of the Connor-Davidson Resilience Scale (CD-RISC) in Competitive Sport (2016, neutral): “However, with a sample size over 200, ShapiroeWilks tests are extremely powerful and small deviations from normality can result in significant test results (Ghasemi & Zahediasl, 2012; Razali & Wah, 2011).”
- Descriptive Statistics and Normality Tests for Statistical Data (2019, neutral): “96 are sufficient to establish normality of the data.[8] However, medium‐sized samples (50≤ n <300), at absolute z‐value ± 3.”
- Parametric or Non-parametric: Skewness to Test Normality for Mean Comparison (2020, neutral): “Besides, it was stated that KS test is not useful and less accurate in practice (Field, 2009; Ghasemi & Zahediasl, 2012; Schucany & Tong NG, 2006).”
- Tumor Microenvironment Characterization in Gastric Cancer Identifies Prognostic and Immunotherapeutically Relevant Gene Signatures (2019, neutral): “Statistical analysis The normality of the variables was tested by the Shapiro—Wilk normality test (47).”