NORMALITY TESTING METHODS AND THE IMPORTANCE OF SKEWNESS AND KURTOSIS IN STATISTICAL ANALYSIS

Authors

Georges Hatem, University of Porto, Portugal, Lebanese University, LebanonFollow
Joe Zeidan, University of Limoges, FranceFollow
Mathijs Goossens, Centre for cancer detectionFollow
Carla Moreira, University of Porto, PortugalFollow

Keywords

Normality, Skewness, Kurtosis, test, normal distribution.

Disciplines

Business | Engineering | Physical Sciences and Mathematics

Abstract

The normal distribution (bell curve or Gaussian distribution) is a distribution that happens commonly in many circumstances. Real-life data rarely, if ever, follow a perfect normal distribution. Many tests are useful to test normality and more particularly skewness and kurtosis tests assess the comparability of a given distribution from a normal distribution. These tests are widely used in statistics, business, and epidemiological data including blood pressure, heights, IQ scores and measurement errors. This report provides a review assessing the essential methods employed for testing normality and highlighting the importance of skewness and Kurtosis in statistics. Moreover, it gives some examples of the importance of normality in epidemiological health studies analysis.

Author ORCID Identifier

Georges Hatem - https://orcid.org/0000-0003-0964-9722

Joe Zeidan - https://orcid.org/0000-0002-6989-7392

Mathijs Goossens - https://orcid.org/0000-0002-6712-2796

Carla Moreira - https://orcid.org/0000-0002-0570-0650

Recommended Citation

Hatem, Georges; Zeidan, Joe; Goossens, Mathijs; and Moreira, Carla (2022) "NORMALITY TESTING METHODS AND THE IMPORTANCE OF SKEWNESS AND KURTOSIS IN STATISTICAL ANALYSIS," BAU Journal - Science and Technology: Vol. 3: Iss. 2, Article 7.
DOI: https://doi.org/10.54729/KTPE9512

ISSN

2959-331X