This paper is concerned with the structural equation modelling of the academic performance in Statistics degree programme.
Structural equation modelling is a class of methodologies that represent hypotheses about variances and covariances of
observed data in terms of structural parameters defined by a theoretical model. It takes a confirmatory approach to the
multivariate analysis of structural theory which specified the causal relations among the multiple observed variables. The
causal pattern of intervariable relations within the theory was specified a priori. Structural equation modelling evaluated
two models – the measurement model and the structural model. The measurement model related observed responses or
indicators to latent variables (confirmatory factor analysis), while the structural model specified relations among latent
variables (path analysis). The direct and indirect effects of personal factor, psychological factor, institutional/environmental
factor, family characteristics, social and religious factor on the academic performance of students were studied. The
academic performance of students remains a top priority for students, parents, educators, researchers, administrators
(management) and government. The extent to which the theoretical model is supported by sample data collected from
undergraduate students of the Department of Statistics, University of Ibadan, was determined. There were 37 observed
variables and 7 latent variables. The result indicated that the attitude of students towards learning had positive direct
impact on academic performance, while psychological factor had negative influence on academic performance. Also, the
structural equation model analysis with four basic fit indices suggested a reasonable model-data fit.