When dealing with data analysis, terminology like univariate, bivariate, and multivariate are frequently used. Let’s try to figure out what these terms signify.
Univariate analysis
Univariate analysis is the process of analyzing data using just one variable, typically a single column or vector of data. This analysis enables us to comprehend the information and discover patterns and trends. Analyzing the weight of a group of people, for example.
Bivariate analysis
Bivariate analysis is analyzing data using just two variables, or, in other words, putting the data into a two-column table. We can find out the link between the variables using this type of analysis. Analyzing data containing temperature and altitude, for example.
Multivariate analysis
The term “multivariate analysis” refers to the process of analyzing data having more than two variables. The data can have any number of columns other than two. We can find out the impacts of all other variables (input variables) on a single variable using this type of analysis (the output variable). Analyzing data on property pricing, which includes information on the homes such as location, crime rate, area, number of floors, and so on, for example.