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31161279
Practical Statistics for Data Scientists: 50 Essential Concepts Using R and Python, Paperback
Item #:
31161279
OMR 23
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What Stands Out
Cross-Platform Tools
Utilizes both R and Python, offering flexibility and accessibility for data scientists, enabling them to choose the best tool for their specific tasks and projects.
Essential Concepts
Covers over 50 critical statistical concepts, ensuring a solid foundation for understanding and applying statistics in real-world data science scenarios, enhancing practical skills.
Practical Examples
Includes practical examples and applications that help translate theoretical concepts into actionable insights, making it easier for readers to apply statistical techniques effectively.
Product Details
- Comprehensive examples in Python for practical statistical guidance
- Bridges the gap between statistical methods and data science in an accessible format
- Emphasizes the importance of exploratory data analysis in data science
- Explains the principles of experimental design for obtaining definitive answers
- Covers key classification and machine learning techniques for data prediction
- Includes unsupervised learning methods for extracting meaning from unlabeled data
| Book format | Paperback |
| Fiction/nonfiction | Non-Fiction |
| Genre | Computing & Internet |
| Publication date | June, 2020 |
| Pages | 360 |
| Reading level | Professional and Scholarly |
| Subgenre | Data Science |
| Edition | 2nd Edition |
| Publisher | O'Reilly Media |
| Original languages | English |
| Language | English |
| Edu focus | Mathematics |
| Is collectible | N |
| Binding type | Perfect Binding |
| Assembled product height | 9.1 in (23.1 cm) |
| Assembled product weight | 1.3 lb (590 grams) |
| Bisac subject heading | Computers |
Who Should Buy?
-
Data Science Students
This book is ideal for students learning data science concepts and wanting practical applications using R and Python.
-
Professional Analysts
Data analysts looking to enhance their statistical knowledge and apply it practically will benefit from this book.
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Self-Learners
Individuals teaching themselves data science can leverage the clear explanations and examples to grasp essential statistical concepts.
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Beginner Statisticians
Those new to statistics may find the content too advanced without a foundational understanding of the subject.
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Advanced Researchers
Experienced researchers may not find new insights or advanced techniques relevant to their work in this book.
-
Non-Technical Readers
Users without a background in programming or statistics may struggle with the technical jargon and examples provided.
Product Description
Practical Statistics for Data Scientists: 50 Essential Concepts Using R and Python, Paperback
About This Item
Introducing "Practical Statistics for Data Scientists: 50 Essential Concepts Using R and Python Edition 2 Paperback" – the comprehensive guidebook that every aspiring and experienced data scientist needs in their arsenal. Authored by Peter Bruce, Andrew Bruce, and Peter Gedeck, this book is an invaluable resource for anyone looking to master the world of data science. With the rapid advancement of technology and the ever-increasing importance of data-driven decision making, proficiency in statistics is no longer optional for data scientists. This book covers 50 essential statistical concepts, providing you with a solid foundation to solve real-world problems using R and Python. Whether you are a beginner just starting on your data science journey or a seasoned professional seeking to expand your knowledge, this book has something for everyone.
The authors have carefully curated the content to ensure that the concepts are presented in a practical and accessible manner, making it easy for readers to grasp and apply statistical techniques. The publication date of May 2020 ensures that this book is up-to-date with the latest advancements and best practices in the field of data science. It is formatted as a paperback, making it convenient for you to carry it with you wherever you go. By delving into the pages of "Practical Statistics for Data Scientists," you will gain a deep understanding of statistical concepts such as hypothesis testing, regression analysis, machine learning, and much more. The authors provide clear explanations, step-by-step examples, and code snippets in R and Python, allowing you to implement what you learn directly in your projects. With its focus on practical application, this book is a must-have for any data scientist.
Gain the knowledge and skills you need to excel in your career, enhance your decision-making abilities, and unlock valuable insights from your data. Don't miss out on this opportunity to enhance your data science toolkit. Order your copy of "Practical Statistics for Data Scientists: 50 Essential Concepts Using R and Python Edition 2 Paperback" today and embark on your journey towards becoming a master data scientist.
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Product Buying Guide
This buying guide is aimed at data scientists and professionals familiar with R or Python programming languages seeking practical statistical guidance. The second edition of 'Practical Statistics for Data Scientists: 50 Essential Concepts Using R and Python' combines statistical principles with data science applications, making it a valuable resource for those aiming to enhance their statistical perspective in an accessible format.
Product Specifications
- Title: Practical Statistics for Data Scientists: 50 Essential Concepts Using R and Python Paperback
- Language: English
- Format: Paperback
- Pages: 348
- Publisher: O'Reilly Media
- Publication Date: October 27, 2020
- ISBN-10: 1491952962
- ISBN-13: 978-1491952962
Key Features
- Provides comprehensive examples in Python
- Guidance on applying statistical methods to data science
- Covers exploratory data analysis and random sampling principles
- Explains experimental design and regression techniques
- Includes key classification and statistical machine learning methods
Usage Scenarios
- Enhancing statistical understanding for data science applications
- Applying statistical methods in real-world data analysis
- Gaining insights into experimental design and regression for data science
- Learning classification and machine learning techniques for predictive analysis
Usage Scenarios
This book competes with similar guides on practical statistics and data science with a focus on R and Python programming languages.
Some User Review
- A user mentions that the examples provided in Python were particularly helpful for applying statistical concepts in data science projects.
- Another user emphasizes that the guidance on experimental design and regression techniques significantly improved their approach to analyzing data.
Competitors
The price of the book reflects its comprehensive coverage of statistical concepts and practical application in data science, making it a valuable investment for professionals seeking to strengthen their statistical skills for data analysis.
Buying Considerations
- Consider the relevance of the content to your specific needs in applying statistical methods to data science projects.
- Evaluate the potential for applying the examples and guidance provided in Python to your data science work.
- Assess the value of the comprehensive coverage of statistical methods and machine learning techniques in relation to the price of the book.
Conclusion
In conclusion, 'Practical Statistics for Data Scientists: 50 Essential Concepts Using R and Python' serves as a valuable guide for data scientists and professionals looking to integrate statistical principles into their data science work, with a focus on practical examples in Python and guidance on applying statistical methods in real-world scenarios.
View LessThis buying guide is aimed at data scientists and professionals familiar with R or Python programming languages seeking practical statistical guidance. The second edition of 'Practical Statistics for Data Scientists: 50 Essential Concepts Using R and Python' combines statistical principles with data science applications, making it a valuable resource for those aiming to enhance their statistical perspective in an accessible format. Continue Reading
Customer Questions & Answers
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Question:
Does the book cover basic statistics?
Answer: Yes, the guide covers basic statistics from a data science perspective. -
Question:
What is the format of the book?
Answer: The book is available in paperback format. -
Question:
Who are the authors of the book?
Answer: The authors of the book are Peter Bruce, Andrew Bruce, and Peter Gedeck.
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