Journal Information
Research Areas
Publication Ethics and Malpractice Statement
To Scholarlink Resource Center
Guidelines for Authors
For Authors
Instructions to Authors
Copyright forms
Submit Manuscript
Call for papers
Guidelines for Reviewers
For Reviewers
Review Forms
Contacts and Support
Support and Contact
List of Issues


Journal of Emerging Trends in Engineering and Applied Sciences (JETEAS)


Article Title: Principal Component Analysis, an Aid to Interpretation of Data. A Case Study of Oil Palm (Elaeis guineensis Jacq.)
by Ekezie Dan Dan

Principal Component Analysis provides an objective way of finding indices so that the variation in the data can be accounted for as concisely as possible. It may well turn out that two or three Principal Components provide a good summary of all the original variables. Consideration of the values of the Principal Components instead of the values of the original variables may then make it much easier to understand what the data have to say. In short, Principal Components Analysis is a means of simplifying data by reducing the number of variables. Although Principal Components Analysis has been well described in a number of texts, the emphasis of the descriptions has been on the underlying theory of the methods and on the methods of computation. Only a limited number of practicable examples of the technique have been published in sufficient detail to enable the reader to gain any facility in the interpretation of the results of the analysis and the necessary background knowledge to the problems is not usually available. In this paper, a case study of the application of Principal Component Analysis to a practical problem is presented and is suggested that there is a need for the extensive application of the existing methods of multivariate analysis over a wide range of problems and subjects, especially in agriculture, in order to test the practical value of the techniques.
Keywords: multivariate analysis, principal component analysis, agriculture, oil palm (Elaeis guineensis Jacq.)
Download full paper

ISSN: 2141-7016

Editor in Chief.

Prof. Gui Yun Tian
Professor of Sensor Technologies
School of Electrical, Electronic and Computer Engineering
University of Newcastle
United Kingdom



Copyright © Journal of Emerging Trends in Engineering and Applied Sciences 2010