Peter Bruce, Andrew Bruce
A key component of data science is statistics and machine learning, but only a small proportion of data scientists are actually trained as statisticians.
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Peter Bruce, Andrew Bruce
A key component of data science is statistics and machine learning, but only a small proportion of data scientists are actually trained as statisticians.
Score based on developer article recommendations — not sales data or reviews.
Distills 50 core statistical concepts into a practical guide for data scientists lacking a formal statistics background.
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It connects data science concepts to practical business value.
Cited by 6 different developers, each bringing their own experience and perspective.
Valued for its practical approach — concepts connect directly to real-world engineering decisions and daily work.
"a good reference is Practical Statistics for Data Scientists: 50 Essential Concepts."
— renanmouraf · How to Learn Machine Learning and Deep Learning: a guide for Software Engineers · Jan 29, 2020
"Practical Statistics for Data Scientists – A great book to get started with the math."
— dct_technology · Why Tomorrow’s UX Designers Must Also Be Data Scientists · Sep 24, 2025
"This book is good for you if you are familiar with the R or Python programming languages and have some prior experience in statistics."
— tut_ml · 4 Best Statistics Books for Data Science in 2021 · Mar 2, 2021
Based on 6 developer article mentions
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