Multivariate Models in Research Work: Various...

Multivariate Models in Research Work: Various Outlooks

Author Name : Sudarshan Roy, Dhiman Ray

ABSTRACT

The topic of the study is Multivariate Models in research works and its various looks.  Through this endeavour an attempt has been taken to evaluate the role of multivariate models in research work. When we analyse something, we use multiple variables. Multivariate model is generally a statistical tool. If we want to analyse the data which is concerning more than one type of dimension or observation then also, we can use multivariate model. With the help of multivariate model, it is also possible to solve problem where it has more than one dependent variable which can be compared with other variables. There is a popular thought about research, that research is to see what everybody has seen and think which nobody else has thought. Here in this endeavour, we will study multivariate analysis, types of multivariate methods, bivariate regression, bivariate co-relation, rank co-relation, multiple linear regression, partial regression, statistical packages, graphical user interface, measures of central tendency, measures of dispersion, measures of relationship, association in case of attributes and also some other measures which has been explained in details. This study is an exploratory in nature. Here as a research methodology, it has actually got a certain plan of action which is actually used to recognize, to choose a method and also scrutinize the data about a relevant subject matter and the methodology. Multivariant models helps the researcher to analyse critically and also to appraise the research project’s accuracy and credibility.  This study will definitely help the researcher to get accustomed and familiar with multivariate models in the field of research work and where various multivariate models are used in the purpose of analyse.

Keywords: Multivariate Models, Research Work, bivariate regression, bivariate correlation, rank correlation, multiple-linear regression, partial correlation, statistical packages.