Impact of Statistics on Data Science

In this, we argue that statistics is one of the fields of greatest significance for developing tools and techniques to find patterns in data and to give a greater understanding of them, as well as the most crucial for analyzing and calculating uncertainty. We provide a summary of several data science architectures that have been developed and talk about how statistics affect certain phases such data collection, enrichment, exploration, modelling, validation, and reporting are all steps in the data-processing pipeline. We also highlight errors made when statistical reasoning is disregarded