Advantages of MANOVA in Multivariate Data Analysis
Advantages of MANOVA in Multivariate Data Analysis
MANOVA provides a scope to the researchers or the statisticians to insert multiple dependent variables, as it is a multivariate model and supports different dependent data variables for further in depth critical analysis and data interpretation. SPSS is an easy statistical software package of using different statistical measures and in this regard, most of the researchers are using MANOVA worldwide to analyse different data variables and evaluate the impacts of the independent variable on the dependent one.
It limits the joint error rate, where the researchers can avoid errors in the data set and progress further for better data management and analysis. Data handling becomes easier with the SPSS help, where it is possible for the researchers or the data analysts to insert the data and handle the large data set by avoiding error value and mission variables in the data set. This further improves the quality of the data variables for performing MANOVA. As MANOVA considers multiple dependent variables, the joint probability of rejecting a true null hypothesis increases with the additional test. The use of MANOVA is helpful for the researchers where the error rate equals the significance level. The access of patterns between the multiple dependent variables is also different from other statistical tests in SPSS, where the factors in the model can affect the relationship between the dependent variables present in the data set, rather than considering only one dependent variable.
MANOVA can also detect the pattern of changing the dependent variables due to the significant changes in the independent variables in the data set. Greater statistical power is another advantage of MANOVA, where it is possible for the researchers or the data analysis to perform the statistical analysis accurately and identify the value of correlation coefficient for evaluating the positive or negative changes in dependent variables due to the changes in the independent variables in the data set. it can also shows the differences in ANOVA tests between the variables as well as the researchers can improve their chances of finding what changes as a result of the experimental treatment in the data set. The statistical analysis is also possible to detect whether the groups differ along a combination of the variables.
Conclusion
It can be concluded that MANOVA is useful for the data analysis or the researchers to test the research hypothesis, in case of multiple dependent variables. Through this reliability analysis, the data analysts can analyse the impacts of the multiple independent variables on the multiple dependent variables in the data set.
