Practical Statistics for Data Scientists: 50+ Essential Concepts Using R and Python, Second Edition (Greyscale Indian Edition)
Product ID: 267605414
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All Indian Reprints of O'Reilly are printed in Grayscale. Statistical methods are a key part of data science, yet few data scientists have formal statistical training. Courses and books on basic statistics rarely cover the topic from a data science perspective. The second edition of this popular guide adds comprehensive examples in Python, provides practical guidance on applying statistical methods to data science, tells you how to avoid their misuse, and gives you advice on what’s important and what’s not. Many data science resources incorporate statistical methods but lack a deeper statistical perspective. If you’re familiar with the R or Python programming languages and have some exposure to statistics, this quick reference bridges the gap in an accessible, readable format. With this book, you’ll learn: Why exploratory data analysis is a key preliminary step in data science How random sampling can reduce bias and yield a higher-quality dataset, even with big data How the principles of experimental design yield definitive answers to questions How to use regression to estimate outcomes and detect anomalies Key classification techniques for predicting which categories a record belongs to Statistical machine learning methods that "learn" from data Unsupervised learning methods for extracting meaning from unlabeled data Review: Good technical book - Superb delivery. Book's very good 👍 Review: Good book - Good book to learn and revise statistics for data science. The code snippets provided in R and Python for each concepts are also helpful.
| Best Sellers Rank | #14,430 in Books ( See Top 100 in Books ) #7 in Statistics |
| Customer Reviews | 4.5 out of 5 stars 1,220 Reviews |
D**J
Good technical book
Superb delivery. Book's very good 👍
R**R
Good book
Good book to learn and revise statistics for data science. The code snippets provided in R and Python for each concepts are also helpful.
P**I
Good for quick revision but not as textbook
Book is barely 300 pages and is very good if you have an interview coming up and want to quickly revise everything in machine learning. But don't expect it to act as a textbook, it's very brief. Also a little expensive considering black and white pages.
A**I
Good
K**T
Excellent book on Statistics for Data Scientists
This is an excellent book which explains the statistics concepts as required for data scientists. Every topic is explained in right sequence. However, some prior understanding or background in basic statistics would help you in grasping the content faster.
R**I
Good buy
The content of the book is excellent and paper quality of the book is good.
H**L
good to have a stats reference
Awesome book. Go for international version if you want good paper quality. Content of the book is good, easy to understand. Not a detailed book.
S**A
Perfect for data scientists (beginners to intermediate)
This is the beat statistics material that summarizes the comcepts well. It is perfect for beginner to intermediate data professionals/scientists. This book is especially for you if you would rather get to the roots of the concept and practical methods rather than work with mathematical symbols and proofs.
A**R
Easy read, covers the basics in a very approachable way.
A very good book, an easy read and covers a lot of basic statistics concepts you would learn in intro to stats university course but in a way more approachable way. If you already good with your stats, you can skip this book. If you feel like stats need improvement, this is a good start.
J**N
Had issues with physical copy but great response from O'Reilly
I had purchased a new physical copy of the book, and realized there were several pages that were blank and missing. I contacted O'Reilly about the problem and they were extremely quick with a resolution! They were able to give me a different copy so I could read it without the missing pages. The content of the book itself is good, except in all black and white, which doesn't bother me personally but may bother someone else when it comes to the graphs. I think the R and Python content are both great, and it keeps the code concise and quick to the point. Great for R beginners, but for python users I would recommend a little more experience. As for the math parts, its great for those who are new to statistics and gives easy to read explanations, and a great refresher for those who just want to review some of the concepts. I especially like the sections provided for further reading, which have been helpful.
F**A
Underwhelming
I was looking forward to reading this book due to the excellent reviews on Amazon, but it failed to deliver. I struggled to understand the intended target audience, as most of the concepts are normally taught in high school-level courses. In all honesty, the hype surrounding this book speaks volumes about the average knowledge of statistics among Data Scientists.
J**S
Muy buen libro
Buen libro con un excelente contenido temático
G**E
Super :)
Everything was great, from the shipping to the packaging.
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