Business Research Methods: Theoretical Demystification of The Use of Multivariate Analysis Techniques in Research

Abstract

Multivariate data analysis techniques observe and analyse multiple statistical variables. These are more advanced than univariate methods (methods that analyse one variable) and bivariate methods (methods that analyse two variables). Multivariate analysis methods were developed to analyse datasets containing multiple variables simultaneously and are ideal for analysing large datasets to reveal causal and effect relationships between variables. This paper identifies different categories of multivariate analysis methods, discusses the assumptions they are based on, analyses their goals and objectives, and describes their advantages and limitations. It also discusses the factors researchers must consider when determining the best technique for a particular research project. The article concludes with a discussion of commonly used methods of multivariate data analysis. This is not a discussion of the statistics underlying each method, but rather an introduction to multivariate methods and their capabilities and limitations in answering research questions.

Keywords: Multivariate analysis, Univariate analysis, Bivariate analysis, ANOVA, MANOVA,

DOI: 10.7176/JEP/14-21-06

Publication date:July 31^st 2023