Practical Statistics for Data Scientists: 50+ Essential Concepts Using R and Python
Product ID: 184711450
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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: 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. Review: Great book - Really a great book for stat. I am really glad I purchased this book. Easy explanation and great examples.
| Best Sellers Rank | #44,861 in Books ( See Top 100 in Books ) #5 in Mathematical & Statistical Software #6 in Data Mining (Books) #9 in Data Processing |
| Customer Reviews | 4.6 out of 5 stars 976 Reviews |
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.
A**R
Great book
Really a great book for stat. I am really glad I purchased this book. Easy explanation and great examples.
M**R
Seriously Great Book
I've taken many stats classes, most of them using R, at the undergraduate and graduate level, and I really wish I found this book before I did. I picked this book up as a refresher, and not only did it succinctly describe all and a bit more of what I learned in those courses, but it has excellent "further readings," great clarifying synonym lists when it defines "key terms," and is very readable. Literally blown away.
F**.
Low print quality
Good content/low quality print
M**1
A book to efficiently come up to speed in Stats and Modern programming
Excellent book to learn statistics and Python or R
S**A
Used but like NEW
Arrived promptly in perfect condition - like new with zero marking!
M**A
Very useful book
The book is amazing and very useful, for beginners also. The most valuable from my point of view is presence of code both for R and Python, which helps understand the syntax better for one language if you know another.
S**N
This is a very good book to start learning Stats for Data Science
This is a very good book to begin your DS stats journey with. I learned more from this book than I did in my DS grad school classes. It covers the basics you'll need everyday in a practical way.
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.
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.
C**E
Ótimo
Entrega super rápida e excelente livro
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