Differentiate between univariate, bivariate and multivariate analysis.

**Univariate analysis:-** provides summary statistics for each field in the raw data set (or) summary only on one variable. *Ex* :- CDF,PDF,Box plot, Violin plot.

**Bivariate analysis:-** is performed to find the relationship between each variable in the dataset and the target variable of interest (or) using 2 variables and finding realtionship between them. *Ex* :-Box plot,Voilin plot.

**Multivariate analysis:-** is performed to understand interactions between different fields in the dataset (or) finding interactions between variables more than 2. *Ex* :- Pair plot and 3D scatter plot.

It’s something strictly related to the analysis you need to conduct. What changes in the branches you mentioned is the number of variables that you analyse.

When you are looking for interactions between observed processes or variables, you are using a multivariate technique, which may include the bivariate case if we treat 2 variables. The content of a multivariate model is fundamentally different from a univariate one, but it is still possible to apply a univariate model to several variable. basically, it’s related to the number of variables and features that you would like to observe.