International Journal of Scientific & Technology Research

IJSTR@Facebook IJSTR@Twitter IJSTR@Linkedin
Home About Us Scope Editorial Board Blog/Latest News Contact Us

IJSTR >> Volume 1 - Issue 9, October 2012 Edition

International Journal of Scientific & Technology Research  
International Journal of Scientific & Technology Research

Website: http://www.ijstr.org

ISSN 2277-8616

On Regression Analysis of The Relationship Between Age And Blood Cholesterol On Blood Pressure

[Full Text]



R. E. Ogunsakin, R. B. Ogunrinde, O. Omotoso , O. B. Adewale



Keywords: Age, systolic, regression, parameters, hypotheses



Abstract:- This paper investigates the relationship of Age and Blood cholesterol on systolic blood pressure. The data used for this paper were obtained from Ekiti State University Teaching Hospital, Ado Ekiti. People wondered if high blood pressure is a function of age or that the effect of high blood cholesterol is manifested in the high blood pressure. A multiple regression analysis was used for the study. At the end of the analysis, Age and systolic blood pressure were seen to have a significant relationship with each other. Also, blood cholesterol and age were found to have significant relationship with systolic blood pressure. The result shows a degree of relationship between the blood pressure and the blood cholesterol. Increase in blood cholesterol signifies increase in blood pressure of a man which can easily lead to an abnormal blood pressure e.g. high blood pressure.



1. Elmer, C.F. 1987. ‘On the theory of correlation’. J Royal SOC

2. Fisher, R. A. 2002. The goodness of fit of regression formulae and Distribution of regression coefficient.

3. Gujarati, D.N. 2003. Basic Econometrics. McGraw Hill: London, UK.

4. Koutsoyiannis, A. 2001. Theory of Econometrics. McMillan Press: London, UK.

5. Miens, G. 2001. Regression towards Hereditary stature

6. Murray, R.S. Theory and problem of statistics in SI Unit. Schaum’s Series

7. Ryan, T.P. 2003. Modern Regression Analysis for Scientists and Engineers. NIST: Washington, DC.

8. Adeleke, R.A, O.Y. Halid, and B.J. Adegboyegun. 2008. “Analysis of Extreme-Value Distribution with Applications to Maximum Temperature Measurements” (Unpublished Article).

9. Smith. R.L. 1985. “Maximum Likelihood Estimation in a Class of Non-Regular Cases”. Biometrika. 72:67-90