Statistical Analysis on the Rate of Kidney (Renal) Failure

Vishwa Nath Maurya^1, , Vijay Vir Singh² and Madaki Umar Yusuf²

¹Professor & Head, Department of Mathematics & Statistics, the University of Fiji, Fiji

²Department of Mathematics and Statistics, Yobe State University, Damaturu, Nigeria

Cite this paper:
Vishwa Nath Maurya, Vijay Vir Singh and Madaki Umar Yusuf. Statistical Analysis on the Rate of Kidney (Renal) Failure. American Journal of Applied Mathematics and Statistics. 2014; 2(6A):6-12. doi: 10.12691/ajams-2-6A-2

Abstract

This paper is based on statistical analysis of rate of kidney renal failure taking into account that the variables of interest are sex and age group. The nature of the data used herein is secondary data, which was obtained from University of Maiduguri Teaching Hospital (UMTH) medical record for consecutive ten (10) years (1998-2007), while monthly reported cases was collected and analyzed. Our present study has been carried out in order to determine whether the effect of renal failure depends on age and sex, and to look at the prevalence of kidney (renal) failure, over the period of study. Appropriate statistical techniques have been used to test the difference of means (t-test) and contingency table (x² -test), based on the analysis of results. The analysis has been done for significant at 5% level of significance. The empirical results are obtained from the tests of two different means which reveal that there is a significant difference in the prevalent of renal failure between male and female. Resultantly, the impact of kidney renal failure has been focused both on two parameters of age and sex. Finally, some significant suggestions based on our empirical results and observations have also been proposed for preventing kidney renal failure and future scope of present study.

Keywords:
Chronic kidney disease (CKD) kidney (renal) failure chi-square test T-test level of significance Yates’s correction Helmert distribution

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