Glossary
Univariate Analysis
The analysis of a single variable at a time, focusing on describing its distribution, central tendency (mean, median, mode), and dispersion (variance, range, IQR). Univariate analysis is typically the first stage of any data exploration and includes graphical tools (histograms...
Definition
The analysis of a single variable at a time, focusing on describing its distribution, central tendency (mean, median, mode), and dispersion (variance, range, IQR). Univariate analysis is typically the first stage of any data exploration and includes graphical tools (histograms, box plots) and summary statistics. It contrasts with bivariate and multivariate analyses, which examine relationships among two or more variables.
Why It Matters
Before modelling relationships between variables, researchers must understand each variable individually. Univariate analysis reveals data quality issues (outliers, missing values, unexpected distributions) and guides the choice of downstream methods. Skipping this step risks applying inappropriate models to poorly understood data.
Example
Before building a regression model for house prices, an analyst examines each variable individually: the distribution of prices is right-skewed with a long tail, the number of bedrooms is roughly normally distributed, and neighbourhood type is a categorical variable with four levels. These insights inform transformations and modelling choices.
Related Terms
Software Notes
- SPSS: Analyze > Descriptive Statistics > Frequencies or Explore; select charts and statistics
- R:
summary(df),hist(),boxplot(),describe()from thepsychpackage - Stata:
summarize variable, detail;histogram variable;tab variablefor categorical