Bivariate analysis is one of the simplest forms of quantitative (statistical) analysis. It involves the analysis of two variables (often denoted as X, Y), for the purpose of determining the empirical relationship between them. Bivariate analysis can be helpful in testing simple hypotheses of association.
Bivariate analysis can help determine to what extent it becomes easier to know and predict a value for one variable (possibly a dependent variable) if we know the value of the other variable (possibly the independent variable) (see also correlation and simple linear regression). Bivariate analysis can be contrasted with univariate analysis in which only one variable is analyzed. Like univariate analysis, bivariate analysis can be descriptive or inferential. It is the analysis of the relationship between the two variables.
Bivariate analysis is a simple (two variable) special case of multivariate analysis (where multiple relations between multiple variables are examined simultaneously).
How to start Bivariate Analysis?
Stage – 1: At this stage there will be cross-tabulation between one demographic and one statement/question.
It is better to start from cross-tabulation between demographic attributes and question statements.
What is cross-tabulation? – Click Here (First Read the explanation of cross tabulation)
Watch video Cross-tabulation in SPSS
Stage – 2: At this stage cross-tabulation between one demographic and one variable (Index). For this You have to theoretically understand the idea of Principle Component Analysis (PCA).