Description: Descriptive statistics is a branch of statistics that deals with the summarization and description of data. Its main objective is to provide a clear and concise summary of the characteristics of a dataset, facilitating the understanding of the information contained within it. This is achieved through various measures, such as mean, median, mode, variance, and standard deviation, which describe the central tendency and dispersion of the data. Additionally, descriptive statistics employs graphical representations, such as histograms, box plots, and scatter plots, to effectively visualize the information. This branch is fundamental in data analysis and interpretation, as it allows analysts and data scientists to gain an overview of the data before applying more complex analysis techniques. Descriptive statistics is not limited to numerical data collection but can also be applied to categorical data, providing a solid foundation for informed decision-making and pattern identification in the data.
History: Descriptive statistics has its roots in antiquity, but its formal development began in the 18th century with the work of mathematicians such as John Graunt and Pierre-Simon Laplace. Graunt, in 1662, published ‘Natural and Political Observations Made upon the Bills of Mortality’, where he used mortality data to perform statistical analyses. Throughout the 19th century, statistics solidified as a scientific discipline, with figures like Karl Pearson and Francis Galton contributing to the development of statistical methods. In the 20th century, descriptive statistics became integrated into various disciplines, from economics to biology, and became an essential tool for research and decision-making.
Uses: Descriptive statistics is used in a wide variety of fields, including scientific research, economics, psychology, sociology, and public health. It allows researchers to summarize and present data in an understandable manner, facilitating the identification of trends and patterns. In the business realm, it is used to analyze sales performance, customer satisfaction, and other key indicators. Additionally, it is fundamental in the preparation of reports and presentations, where a clear representation of data is required.
Examples: An example of descriptive statistics is the analysis of exam results in a class. A teacher may calculate the mean, median, and mode of the grades to understand the overall performance of the students. Another example is the use of bar charts to show the distribution of consumer preferences in a market survey, allowing companies to identify which products are most popular.
