Principal component analysis: programming and application

Date

2024

Degree

Bachelor of Science in Agriculture

College

College of Arts and Sciences (CAS)

Adviser/Committee Chair

Manuel M. Manuel, Jr.

Abstract

Statistical principles behind principal component analysis as a multivariate procedure and its application to nine socio-economic variables were illustrated. Educational attainments et both the head and children in a household had the highest weights or loadings on the first component, tenure status on the second component, size of the family and food consumption on the third component, thus indicating the magnitude of effects of these variables on the total variability of each component or factor. However, the analysis done on both covariance and correlation matrices did not, in general, distinctly pool the variables most associated with one another. This was attributed to the low intercorrelations and observed relative similarity in variances among the variables which represented some of the characteristics of a rural population. The extraction of components and their variances was facilitated by a computer program suited for the IBM 1620.

Language

English

Location

UPLB Main Library Special Collections Section (USCS)

Call Number

Thesis

Document Type

Thesis

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