The title Essential Statistics for Non-STEM Data Analysts speaks for it. It teaches the essential statistics to non-stem people who wish to pursue a career in data analysis or data science. The contents of this book is an organic mixture of python programming, theoretical statistics knowledge and detail-oriented example walk-throughs.
The story and an overview of my book Essential Statistics for Non-STEM Data Analysts
The story of this book is actually pretty inspiring. Around December 2019, while I was waiting for my OPT to get approved, I wanted to do something more meaningful and productive. I often went to a local library in Culver City, Los Angeles and absolutely loved it and the community of book lovers. I walked to the counter and said to the manager that I wanted to offer a free mini course of data science to the library patrons as a fan of the library.
Later, we agreed on the format, the poster design, etc. In January 2020, the 7-week mini course started. About 10 patrons and I met every Tuesday late afternoon to cover topics including Python programming, basic statistics, webs scraping, visualization and even natural language processing. I carefully created the content and ensured the high quality of it. The audience loved it. Another librarian from a library in Monterey park even invited me to offer the mini course at her library. Unfortunately the COVID-19 forbade that and I began to work at ISI which limited my availability as well.
Well, I discovered that there is a big gap in the background knowledge and even the vocabulary usage between people who received formal STEM training like me (master in electrical engineering and an unfinished PhD ABD in physics) and people who are not very comfortable with math. How to help people who are making this transformation into the analytics era?
I did some research and found out that no existing books in the market met the goal of filling this gap. In my opinion, you have to speak the language of your audience, without distorting your original meaning, to be heard and understood. So I drafted a book proposal and wrote a sample chapter, submitted to a book editor I found on LinkedIn and the rest is just the long long time of writing, editing and rewriting, etc.
This book is designed for non-STEM people. If you don’t have a STEM major or didn’t get college education at all, this book is for you.
You need some essential Python programming skills to reproduce the examples in the book. If you don’t have any experience in Python, this page will give you a quick start. The notebooks for the code in the book is in this repository.
If the readers are experienced in data science or machine learning, there is no need for you to read this book. Please don’t give a bad rating on Amazon because it is too easy. Instead, I recommend the following books to such readers.
Well, I am closely monitoring the review of the book on Amazon, comments from my friends, students and colleagues. I plan to keep updating the book’s content so it reflects the market’s need for data analysts and scientists. Feel free to reach out to me to provide your insights. Your name will show up in future editions' preface 😀.