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Asian Journal of Probability and Statistics, .,Vol.: 1, Issue.: 2

Review Article

Comparison of Goodness of Fit Tests for Normal Distribution


I. Agu, Friday1,2* and E. Francis, Runyi3

1Department of Statistics, University of Calabar, Calabar, Nigeria.

2Department of General Studies, Cross River State Institute of Management and Technology (ITM), Ugep, Nigeria.

3Department of Mathematics, Arthur Jarvis University, Akpabuyo, Cross River State, Nigeria.

Article Information


(1) Seemon Thomas, Associate Professor, Department of Statistics, St. Thomas College, Pala, Mahatma Gandhi University, India.

(2) Halim Zeghdoudi, Departememt of Mathematics, Badji-Mokhtar University, Algeria.

(3) Manuel Alberto M. Ferreira, Professor, Department of Mathematics, ISTA-School of Technology and Architecture, Lisbon University, Portugal.


(1) Fellah Mamoun, Mechanical Engineering Department, Abbes Laghrour University, Algeria.

(2) Stamatis Papadakis, University of Crete, Greece.

(3) Jiajuan Liang, University of New Haven, USA.

(4) Bilge Peker, Necmettin Erbakan University, Turkey.

(5) Luis Angel Gutierrez-Mendez, Autonomous University of Puebla, Mexico.

Complete Peer review History: http://www.sciencedomain.org/review-history/25080


Goodness of fit test is a test that has attracted researchers’ interest over the decades. This study is on goodness of fit test for normal distribution only. The Kolmogorov-Smirnov (K-St) and Pearson’s Chi-square (χ² test) goodness of fit test were used to determine the normality of a given data.  The result revealed that the data is normal under the two tests and that the Kolmogorov-Smirnov (K-S test) were preferred to Pearson’s Chi-square (χ² test). The Kolmogorov-Smirnov (K-S) test of goodness of fit is the most suitable in terms of the p-value.

Keywords :

Normal distribution, Kolmogorov-Smirnov goodness of fit test, Chi square goodness of fit test, p-value.

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