Importance of Statistics for Data Mining and Data Science
Vítor Ribeiro, André Dionísio Rocha, Rui Peixoto, Filipe Portela, Manuel Filipe Santos · 2017
Knowledge has been significantly recognized by managers as an important asset for organizations. This recognition stems from the fact that knowledge is increasingly used as a strategic resource to create competitive advantage, improve organizational processes, reduce costs, and more. Data Mining (DM) is an area of study that facilitates that process, allowing you to extract useful information and predictions from the vast data sets produced by the company. With the help of statistics and their mathematical methods, DM has gradually become important and useful. Some of the main statistical metrics used to perform data analysis are mean, median, variance, standard deviation, variance analysis, correlation and regression. This study aims to highlight and prove the importance of statistics in DM, which has so much potential in terms of creating a competitive advantage on behalf of the companies. A case study using Intensive Care Medicine data were chosen to prove the importance of statistics for Data Mining.