Mathematics and Statistics Vol. 8(6), pp. 683 - 692
DOI: 10.13189/ms.2020.080608
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Comparison of Rank Transformation Test Statistics with Its Nonparametric Counterpart Using Real-Life Data

Adejumo T. Joel. ^1,*, Omonijo D. Ojo ^2,3, Owolabi A. Timothy ¹, Okegbade A. Ibukun ¹, Odukoya A. Jonathan ⁴, Ayedun C. Ayedun ^5
1 Department of statistics, Ladoke Akintola University of Technology, Ogbomoso Oyo State, Nigeria
² Department of Student Industrial Work Experience Scheme, Covenant University, Nigeria
³ Department of Sociology, Olabisi Onabanjo University, Ago-Iwoye, Nigeria
⁴ Department of Psychology, Covenant University, Ota, Nigeria
⁵ Department of Estate Management, Covenant University, Ota, Nigeria

ABSTRACT

Over the years, non-parametric test statistics have been the only solution to solve data that do not follow a normal distribution. However, giving statistical interpretation used to be a great challenge to some researchers. Hence, to overcome these hurdles, another test statistics was proposed called Rank transformation test statistics so as to close the gap between parametric and non-parametric test statistics. The purpose of this study is to compare the conclusion statement of Rank transformation test statistics with its equivalent non parametric test statistics in both one and two samples problems using real-life data. In this study, (2018/2019) Post Unified Tertiary Matriculation Examinations (UTME) results of prospective students of Ladoke Akintola University of Technology (LAUTECH) Ogbomoso across all faculties of the institution were used for the analysis. The data were subjected to nonparametric test statistics which include; Asymptotic Wilcoxon sign test and Wilcoxon sum Rank (both Asymptotic and Distribution) using Statistical Packages for Social Sciences (SPSS). In the same vein, R-statistical programming codes were written for Rank Transformation test statistics. Their P-values were extracted and compared with each other with respect to the pre-selected alpha level (α) = 0.05. Results in both cases revealed that there is a significant difference in the median of the scores across all faculties since their type I error rate are less than the preselected alpha level 0.05. Therefore, Rank transformation test statistics is recommended as alternative test statistics to non-parametric test in both one sample and two-sample problems.

KEYWORDS
Rank Transformation, Parametric, Non-parametric, Normal Distribution, Test Statistics

Cite This Paper in IEEE or APA Citation Styles
(a). IEEE Format:
[1] Adejumo T. Joel. , Omonijo D. Ojo , Owolabi A. Timothy , Okegbade A. Ibukun , Odukoya A. Jonathan , Ayedun C. Ayedun , "Comparison of Rank Transformation Test Statistics with Its Nonparametric Counterpart Using Real-Life Data," Mathematics and Statistics, Vol. 8, No. 6, pp. 683 - 692, 2020. DOI: 10.13189/ms.2020.080608.

(b). APA Format:
Adejumo T. Joel. , Omonijo D. Ojo , Owolabi A. Timothy , Okegbade A. Ibukun , Odukoya A. Jonathan , Ayedun C. Ayedun (2020). Comparison of Rank Transformation Test Statistics with Its Nonparametric Counterpart Using Real-Life Data. Mathematics and Statistics, 8(6), 683 - 692. DOI: 10.13189/ms.2020.080608.