Factor analysis programming and application

Date

4-1972

Degree

Bachelor of Science in Applied Mathematics

College

College of Agriculture and Food Science (CAFS)

Adviser/Committee Chair

Manuel M. Manuel, Jr.

Abstract

Maximum Likelihood factor analysis was illustrated and applied to socio-economic data. Principal axis eigenvectors were used as the first approximation of the maximum likelihood factor loadings.

The correlation matrix showed that most variables were uncorrelated. This explained why nine significant factors were found from nine variable at one percent level of significance.

A fORTRAN II program for the IBM 1620 and its auxillaries was designed to carry out the required computations.

Language

English

Location

UPLB Main Library Special Collections Section (USCS)

Call Number

Thesis

Document Type

Thesis

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