Generally, Multivariate Analysis or Multivariate Method relates to statistical methods which simultaneously conducting analysis towards more than 2 variables on every object or people.
Therefore, multivariate analysis is the expansion of univariate analysis (like t test) or bivariate analysis (like correlation test and simple regression).
Multivariate analysis is defined as multi variable analysis in one or more than one relationship. Such analysis relates to every statistical technique which is simultaneously analyzing a number of individual and object measurement.
For example, if we conduct a simple regression analysis, with a Y variable and an X variable, then such analysis is considered as bivariate analysis, due to the existence of two (bi) variable, X and Y.
In the other side, if we conduct double regression analysis, with a Y variable and two X variables (X1 and X2), it will be considered as multivariate one, because there are three variables (including X1 and X2).
Variate can also be defined as a linear combination from variables which empirically have qualities.
As an example, the following is double regression equation :
Variate value : w1.X1+w2.X2+w3.X3+...+wn.Xn
Here, Xn is established variable, while wn is result from multivariate process. Variate value defined as the result of multiplying and summating of w and X, which results a certain variate value.
In practice, data types or variable types determine which multivariate method will be used. Practically, type of X1 should be figured out first, and so on.
Mistake in selecting the best method, based on the data type which makes result of the data processing biased. It is also applied in multivariate statistical method selection, as it is applied in bivariate and univariate one.
