Difference between Univariate, Bivariate and Multivariate Analysis
The basic difference between univariate, bivariate, and multivariate analysis is explained in the table added below:
Univariate Analysis |
Bivariate Analysis |
Multivariate Analysis |
---|---|---|
Univariate analysis involves the analysis of a single variable. This helps to describe and summarize the characteristics and distribution of that variable. |
Bivariate analysis involves the analysis of the relationship between two variables. This helps to examines how one variable behaves in relation to another. |
Multivariate analysis involves the simultaneous analysis of three or more variables. This helps to examines the complex relationships between multiple variables. |
Techniques used in univariate analysis include:
|
Techniques used in bivariate analysis include
|
Common techniques used in multivariate analysis include:
|
Univariate analysis is useful for understanding the basic properties of a variable and identifying any outliers or patterns within it. |
Bivariate analysis helps in understanding the strength and direction of the relationship between two variables. It is particularly useful for identifying associations or dependencies between variables. |
Multivariate analysis allows for the exploration of interactions and dependencies among multiple variables. It helps in understanding the combined effect of several variables on an outcome or in identifying latent structures within the data. |
Bivariate Analysis
Bivariate analysis examines the relationship between two variables. It is often denoted as X and Y. It helps uncover correlations and associations between different factors in data analysis.
In this article, we will understand the meaning of bivariate analysis and its definition, as well as the types of bivariate analysis and applications of bivariate analysis.