A Study on Sensitivity and Robustness of One Sample Test Statistics to Outliers

α
Adejumo Taiwo Joel
Adejumo Taiwo Joel
σ
Kayode Ayinde
Kayode Ayinde
ρ
Taiwo Joel Adejumoand
Taiwo Joel Adejumoand
Ѡ
Gbenga Sunday Solomon
Gbenga Sunday Solomon
α Ladoke Akintola University of Technology Ladoke Akintola University of Technology

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A Study on Sensitivity and Robustness of One Sample Test Statistics to Outliers

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Abstract

Outliers are observations that stand too different from others in a set of observations. When present in a data set, they affect both descriptive and inferential statistics. This work therefore, studies the sensitivity and robustness of one sample test statistics to outliers so as to know the appropriate one to test hypothesis about the population parameter when outliers are present. One sample test statistics considered are: parametrics test (Student t-test and z-test), non-parametric test (Wilcoxon Sign test (Distribution Sign test (DST), Asymptotic Sign test (AST)), Wilcoxon Signed rank test (Distribution Wilcoxon Signed rank test (DWST) and Asymptotic (AWST)), t-test for rank transformation (Rt-test) and Trimmed t-test statistics (Tt-test). Monte Carlo experiments, replicated five thousand (5000) times, were conducted at eight (8) sample sizes (10, 15, 20, 25, 30, 35, 40 and 50) by simulating data from normal distribution. At each of the sample sizes, 10% and 20% of the generated data were randomly selected and invoked with various magnitude of outliers (-10, -9, -8,… 8, 9, 10).

References

16 Cites in Article
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Funding

No external funding was declared for this work.

Conflict of Interest

The authors declare no conflict of interest.

Ethical Approval

No ethics committee approval was required for this article type.

Data Availability

Not applicable for this article.

How to Cite This Article

Adejumo Taiwo Joel. 2017. \u201cA Study on Sensitivity and Robustness of One Sample Test Statistics to Outliers\u201d. Global Journal of Science Frontier Research - F: Mathematics & Decision GJSFR-F Volume 16 (GJSFR Volume 16 Issue F6): .

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Issue Cover
GJSFR Volume 16 Issue F6
Pg. 99- 112
Journal Specifications

Crossref Journal DOI 10.17406/GJSFR

Print ISSN 0975-5896

e-ISSN 2249-4626

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GJSFR-F Classification: MSC 2010: 13P25
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v1.2

Issue date

January 19, 2017

Language
en
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Outliers are observations that stand too different from others in a set of observations. When present in a data set, they affect both descriptive and inferential statistics. This work therefore, studies the sensitivity and robustness of one sample test statistics to outliers so as to know the appropriate one to test hypothesis about the population parameter when outliers are present. One sample test statistics considered are: parametrics test (Student t-test and z-test), non-parametric test (Wilcoxon Sign test (Distribution Sign test (DST), Asymptotic Sign test (AST)), Wilcoxon Signed rank test (Distribution Wilcoxon Signed rank test (DWST) and Asymptotic (AWST)), t-test for rank transformation (Rt-test) and Trimmed t-test statistics (Tt-test). Monte Carlo experiments, replicated five thousand (5000) times, were conducted at eight (8) sample sizes (10, 15, 20, 25, 30, 35, 40 and 50) by simulating data from normal distribution. At each of the sample sizes, 10% and 20% of the generated data were randomly selected and invoked with various magnitude of outliers (-10, -9, -8,… 8, 9, 10).

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A Study on Sensitivity and Robustness of One Sample Test Statistics to Outliers

Kayode Ayinde
Kayode Ayinde
Taiwo Joel Adejumoand
Taiwo Joel Adejumoand
Gbenga Sunday Solomon
Gbenga Sunday Solomon

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