Book Image

Essential Statistics for Non-STEM Data Analysts

By : Rongpeng Li
Book Image

Essential Statistics for Non-STEM Data Analysts

By: Rongpeng Li

Overview of this book

Statistics remain the backbone of modern analysis tasks, helping you to interpret the results produced by data science pipelines. This book is a detailed guide covering the math and various statistical methods required for undertaking data science tasks. The book starts by showing you how to preprocess data and inspect distributions and correlations from a statistical perspective. You’ll then get to grips with the fundamentals of statistical analysis and apply its concepts to real-world datasets. As you advance, you’ll find out how statistical concepts emerge from different stages of data science pipelines, understand the summary of datasets in the language of statistics, and use it to build a solid foundation for robust data products such as explanatory models and predictive models. Once you’ve uncovered the working mechanism of data science algorithms, you’ll cover essential concepts for efficient data collection, cleaning, mining, visualization, and analysis. Finally, you’ll implement statistical methods in key machine learning tasks such as classification, regression, tree-based methods, and ensemble learning. By the end of this Essential Statistics for Non-STEM Data Analysts book, you’ll have learned how to build and present a self-contained, statistics-backed data product to meet your business goals.
Table of Contents (19 chapters)
1
Section 1: Getting Started with Statistics for Data Science
5
Section 2: Essentials of Statistical Analysis
10
Section 3: Statistics for Machine Learning
15
Section 4: Appendix

Chapter 13: Exercises and Projects

This chapter is dedicated to exercises and projects that will enhance your understanding of statistics, as well as your practical programming skills.

This chapter contains three sections. The first section contains exercises that are direct derivatives of the code examples you saw throughout this book. The second section contains some projects I would recommend you try out; some of these will be partially independent of what we covered concretely in previous chapters. The last section is for those of you who want to dive more into the theory and math aspects of this book. Each section is organized according to the contents of the corresponding chapter.

Once you've finished this final chapter, you will be able to do the following:

  • Reinforce your basic knowledge about the concepts and knowledge points that were covered in this book
  • Gain working experience of a project's life cycle
  • Understand the math and theoretical...