Description: Univariate distribution refers to the analysis of a single variable in a dataset. This type of distribution allows for observing and understanding how the values of that specific variable are distributed, providing information about its central tendency, dispersion, and shape. In the context of data visualization, univariate distribution can be represented through histograms, box plots, and density plots, among others. These graphs help identify patterns, such as the presence of skewness, the existence of outliers, and the overall shape of the distribution, whether normal, skewed, or multimodal. Univariate distribution is fundamental in descriptive statistics, as it allows for summarizing and describing the characteristics of the data effectively. Additionally, it is a crucial step in exploratory data analysis, where the goal is to understand the nature of the data before applying more complex techniques. In summary, univariate distribution is an essential tool for any data analyst, as it provides a solid foundation for the interpretation and subsequent analysis of the data.
