Essential Statistics for Non-STEM Data Analysts: Get to grips with the statistics and math knowledge needed to enter the world of data science with Python

This comprehensive guidebook, "Essential Statistics for Non-STEM Data Analysts," is a must-read for anyone looking to gain a solid understanding of data analysis from a statistical perspective.

With a focus on practical applications and real-world examples, this book covers the entire data analysis pipeline, providing readers with the skills and knowledge necessary to extract meaningful insights from their data using Python programming. From preprocessing data and inspecting distributions and correlations to building a solid foundation in statistics for data science and machine learning, this book provides a detailed overview of the mathematical concepts and statistical methods required for undertaking data science tasks.

With a focus on practical applications, readers will learn how to implement statistical methods in key machine learning tasks such as classification, regression, tree-based methods, and ensemble learning. By the end of this book, readers will have gained the knowledge and skills necessary to build and present a self-contained, statistics-backed data analysis report that can be used to inform business decisions and drive growth.

With its focus on practical applications and real-world examples, "Essential Statistics for Non-STEM Data Analysts" is an essential resource for anyone looking to gain a solid understanding of data analysis from a statistical perspective.