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Cited by 396

The DOI matches its Crossref record; 31 of the 31 references it cites were found in a registry or an index.

A Brief Review of Tests for Normality

Open access
Rani Das, Keya·2016·American Journal of Theoretical and Applied Statistics
DOI 10.11648/j.ajtas.20160501.12
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Abstract

In statistics it is conventional to assume that the observations are normal. The entire statistical framework is grounded on this assumption and if this assumption is violated the inference breaks down. For this reason it is essential to check or test this assumption before any statistical analysis of data. In this paper we provide a brief review of commonly used tests for normality. We present both graphical and analytical tests here. Normality tests in regression and experimental design suffer from supernormality. We also address this issue in this paper and present some tests which can successfully handle this problem.

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Metadata

Authors
Rani Das, K.
Venue
American Journal of Theoretical and Applied Statistics
Publisher
Science Publishing Group
Published
2016
Volume
5
Issue
1
Pages
5
ISSN
2326-8999 (ISSN-L)
DOI
10.11648/j.ajtas.20160501.12
OpenAlex
W2266306456
Cited by
396
References
31
FWCI
15.58
Type
journal article
Language
en
Open access
hybrid

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CoChat. (2026). Citation check: A Brief Review of Tests for Normality. https://app.cochat.ai/papers/10.11648/j.ajtas.20160501.12
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Rani Das, K. (2016). A Brief Review of Tests for Normality. American Journal of Theoretical and Applied Statistics. https://doi.org/10.11648/j.ajtas.20160501.12

Data sources

Bibliographic data: Semantic Scholar, OpenAlex, Crossref.

Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).

Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.