Univariate analysis is concerned with the description or summarization of individual variables in a given data set. Univariate analysis is the first step of data analysis once a data set is ready. Univariate Analysis provides a way to produce the most useful statistics. Multivariate analysis is quantitative analysis which examines three or more variables at the same time. The appropriate statistic depends on the level of measurement. Where a researcher wants to report the data on one variable, univariate analysis is used. A researcher may also perform univariate analysis so as to facilitate more complicated analyses, like bivariate analysis and regression analysis. There are graphical and numerical methods for conducting univariate analysis. Univariate analysis can be used when analyzing variation in a data set in which there is only a single variable parameter of interest.
In univariate analysis we explore each variable separately in a data set. To present the information in a more organized format, start with univariate descriptive statistics for each variable. Univariate analysis looks at the range of values, as well as the central tendency of the values. Univariate analysis is a form of quantitative analysis of data where each variable is analyzed in isolation. Univariate analysis is the first procedure one does when examining data being used for the first time. Univariate analysis is the simplest form of statistical analysis. The main purpose of univariate analysis is to describe the data and find patterns that exist within it.
Univariate Analysis describes the pattern of response to the variable and describes each variable on its own. Univariate analysis descriptive statistics can summarize large quantities of numerical data and reveal patterns in the raw data.