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Practical Statistics for Data Scientists is a must-read for anyone who wants to implement statistical methods in practical data science projects. Comprehensive examples in R and Python are included, and the book's focus on the practical aspects of statistics is refreshing.
| Publisher | O'Reilly Media |
| Publication date | June 16, 2020 |
| Edition | 2nd |
| Language | English |
| Print length | 360 pages |
| ISBN-10 | 149207294X |
| ISBN-13 | 978-1492072942 |
| Item Weight | 1.35 pounds (610 grams) |
| Dimensions | 7 x 0.9 x 9.1 inches (17.8 x 2.3 x 23.1 cm) |
Ideal for those entering the field, offering foundational statistical concepts applied in R and Python.
Beneficial for current data analysts seeking to enhance their statistical skills and improve their data insights.
Perfect for undergraduate or graduate students who need practical applications of statistics in data science.
Not suitable for individuals with no programming background, as concepts require familiarity with R and Python.
Practical Statistics for Data Scientists: 50+ Essential Concepts Using R and Python
The book, although having good content, disappointed some customers due to its low quality print. The illustrations printed in black and white looked faded and the paper quality was cheap. However, the technical content was comprehensive and informative. One customer was pleased with the fast and efficient service they received after receiving a book with missing pages. The book covers R and Python content with concise and quick-to-the-point code. The book is great for beginners and those new to statistics but provides a great refresher to those looking to review some concepts. The book emphasizes practical application of statistical concepts and is great for those who want to understand the meaning behind statistical tools and applications before getting into the mathematical weeds.
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