Introduction

Multivariate ANOVA (MANOVA) is the multivariate model of analysis of variance (ANOVA) that accesses multiple dependent variables simultaneously, in order to analyse the impacts of the independent variables on the dependent variables. There are multiple numbers of dependent and independent variables and the ANOVA statistical analysis is being utilised by a wide number of researchers, statisticians and students in order to conduct in depth data analysis and evaluation. The article focuses on understanding the practice of MANOVA in doing SPSS data analysis, and after understanding MANOVA in statistical tests, it would be possible to review the advantages of using MANOVA.

Through critical understanding, it is hereby possible to analyse the use of MANOVA in different statistical analytical programs in order to test the hypothesis and progress further in drawing the final conclusion of the research. The MANOVA mainly analyses the differences between three or more group means and compares it to test the hypothesis, by evaluating whether there is correlation between the dependent and independent variables or not. In ANOVA, it can be accessed with only one dependent variable and in MANOVA, it is possible to analyse the situation with multiple independent and dependent variables.

Advantages of using MANOVA in SPSS Analysis

The statistical procedure of MANOVA provides a solution for the studies and tests the hypothesis of the research by in depth statistical analysis and critical evaluation. SPSS is being utilised to perform MANOVA by considering multiple variables, both the independent and dependent variables in the model. SPSS is the easiest statistical software, in which different statistical measures can be performed by considering the dependent and independent variables. This statistical method of MANOVA test multiple dependent variables at the same time, and by doing so, MANOVA can offer several advantages over other statistical tools.

MANOVA can detect the patterns between the multiple dependent variables, whereas ANOVA only considers only one dependent variable in the data set. Comparing the group mean values, measuring the impacts of the independent variables on the multiple dependent variables is hereby possible under MANOVA. The multivariate approach of MANOVA tests is effective for the researchers or the statisticians to represent different dependent variables efficiently through the graphs, where it is possible to analyse the changes in the dependent variables due to changes in the independent variables at a specific period of time.

The correlation coefficient can be measured with the help of MANOVA, and the researchers or the statisticians are also able to test the alternative and null hypothesis for drawing the final conclusion of the research. MANOVA is hereby beneficial for testing the statistical models with multiple dependent variables. The correlation structure between the dependent variables provides additional information to the model, which gives MANOVA the capability to test the hypothesis and analyse the impacts of the independent variables on the dependent variables. MANOVA is a one of the easy statistical model, where the researchers or the statisticians are using SPSS for in depth critical analysis and data interpretation.