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Five Must-Read Statistics Books to Become a Successful Data Analyst

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Five Must-Read Statistics Books to Become a Successful Data Analyst

If you are looking for a one-shoe-fits-all answer to your data science questions, you won’t find it. But, these books will certainly get you started.

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Statistics, the most crucial branch of data science, is often taught in a bottom-up, theory-first manner, which makes it extremely difficult for students to initially grasp the intricacies of many topics in the discipline. Many students struggle to compose their assignments on percentiles, quarreler, or sample theories and have to ask for help from experts.

It’s okay to fall back on professional tutors once in a while, but it is advisable to refrain from making it a habit. A tutor will surely guide you with your assignments, but it's useful to learn to handle those tricky derivations on your own.

To ease your worries, our team we compiled a list of five essential books that are of paramount importance for any statistician.

If you are looking for a one-shoe-fits-all answer to your data science questions, you won’t find it. You will need to invest sufficient time with many different resources and tools in order to become a pro in applied statistics. We recommend you start with one resource and make sure you have a strong understanding of its concepts before proceeding onto the next one.

Naked Statistics: Stripping the Dread From the Data by Charles Wheelan

This book can be a lifesaver for beginners. Wheelan clarifies essential concepts like inference, correlation, and regression analysis without indulging in any arcane or technical details. He focuses on underlying intuitions that drive statistical analysis.

The Signal and the Noise: Why So Many Predictions Fail – but Some Don’t by Nate Silver

In this book, Silver investigates the possibilities of distinguishing a true signal from the universe of noisy data. He discusses the prediction paradox and attempts to elaborate on factors that help readers to improve the chances of making accurate predictions.

All of Statistics: A Concise Course in Statistical Inference by Larry Wasserman

Want to learn about non-parametric curve estimation, bootstrapping, and classification? Make the learning process easier with this book by Larry Wasserman. Fair warning, the book is written with an assumption that the reader is acquainted with basic calculus and a little linear algebra.

Statistics in Plain English by Timothy C. Urdan

This is an introductory textbook that will help you to gain a better understanding of fundamental statistical functions and methods to interpret them correctly. This book takes you through the basic level statistics (central tendency and describing distributions) and gradually introduces you to more advanced concepts (t-tests, regression, repeated measures ANOVA, and factor analysis).

Practical Statistics for Data Scientists: 50 Essential Concepts by Peter Bruce and Andrew Bruce

This practical guide by Peter and Andrew Bruce will serve as the best statistics homework help if you are looking for a book that covers all the essential statistics topics from a data science perspective. It gives you advice on the most important concepts and talks about the unimportant ones.

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big data ,data structures ,statistics ,books ,reading list ,data analysis ,data analyst

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