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Practical Statistics for Data Scientists: 50 Essential Concepts
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Practical Statistics for Data Scientists: 50 Essential Concepts
Practical Statistics for Data Scientists: 50 Essential Concepts 1st Edition provides essential statistical methods for data science
Practical Statistics for Data Scientists: 50 Essential Concepts
Item #: 3526794

Practical Statistics for Data Scientists: 50 Essential Concepts

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Item #: 3526794

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Practical Statistics for Data Scientists: 50 Essential Concepts 1st Edition provides essential statistical methods for data science
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What Stands Out

Essential Concepts
Covers 50 vital statistical concepts tailored for data scientists, ensuring a solid foundation to analyze data effectively and draw meaningful conclusions in real-world scenarios.
Practical Applications
Focuses on practical applications of statistics in data science, bridging theory and practice to enhance problem-solving capabilities and improve data-driven decision-making.
Accessible Format
Written in a clear and accessible style, making complex statistical concepts understandable for both novice and intermediate data scientists, fostering better learning and retention.

Product Details

Explore 50 essential concepts of practical statistics for data scientists at Ubuy Bahrain. Gain in-depth knowledge and apply statistical techniques in real-world scenarios.
  • Practical guide explaining the application of statistical methods to data science
  • Emphasis on exploratory data analysis and random sampling to reduce bias
  • Covers principles of experimental design, regression, key classification techniques, and statistical machine learning methods
  • Accessible resource for data scientists familiar with R programming language and some statistics exposure
  • Highlights key statistical concepts relevant to data science and their importance
  • Aims to bridge the gap between statistics and data science in an easily referenced format
Publisher O'Reilly Media
Publication date June 27, 2017
Edition 1st
Language English
Print length 315 pages
ISBN-10 1491952962
ISBN-13 978-1491952962
Item Weight 1.12 pounds (510 grams)
Dimensions 6.75 x 0.5 x 9 inches (17.1 x 1.3 x 22.9 cm)

Who Should Buy?

Suitable For
  • Aspiring Data Scientists

    Ideal for beginners seeking foundational statistical concepts necessary for data analysis and interpretation in data science.

  • Statistical Practitioners

    Useful for practitioners looking to brush up on vital statistical principles and enhance their analytical skills effectively.

  • Students in Analytics

    Perfect for students in analytics or data science courses needing a practical guide to statistics relevant to their studies.

Not Suitable For
  • Advanced Statisticians

    May not suit advanced statisticians who require in-depth theoretical insights beyond foundational and practical statistical concepts.

  • Non-technical Readers

    Not suitable for those without a background in statistics as it assumes some familiarity with statistical techniques and terms.

  • Casual Learners

    Could be overwhelming for casual readers or hobbyists seeking a light introduction to statistics without technical depth.

Product Description

About This Item

Introducing the must-have resource for every data scientist: Practical Statistics for Data Scientists: 50 Essential Concepts, 1st Edition. This comprehensive guide is designed to equip both aspiring and experienced data scientists with the statistical knowledge and skills they need to excel in their field. Written by renowned experts in the field, this book covers 50 essential statistical concepts that are directly applicable to the work of data scientists. From probability and sampling to hypothesis testing and regression analysis, each concept is explained in a clear and concise manner, making it easy for readers to grasp and apply to real-world scenarios. Whether you're just starting out in the field or looking to brush up on your statistical skills, this book is an invaluable resource.

It provides practical examples, case studies, and exercises that allow you to practice and reinforce your understanding of each concept. You'll also find helpful tips and tricks, as well as pitfalls to avoid, ensuring that you can confidently apply statistical techniques to your data analysis projects. Practical Statistics for Data Scientists is not just a book, it's a complete learning package. With online resources, including tutorials, training materials, and additional case studies, you'll have everything you need to deepen your understanding of statistics and enhance your data science skills. Whether you're a data scientist, a student studying data science, or a professional looking to expand your skillset, Practical Statistics for Data Scientists is the ultimate guide to mastering statistics in the context of data science.

Don't miss out on this essential resource – order your copy today and take your data science expertise to the next level.

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Customer Questions & Answers

  • Question: What are the main topics covered in 'Practical Statistics for Data Scientists'?

    Answer: The book covers essential statistics concepts tailored for data science, including probability distributions, hypothesis testing, regression analysis, and statistical modeling. It emphasizes practical applications of these concepts in data-driven decision-making. These topics help data scientists understand data better and make informed predictions, ultimately enhancing their analytical skills in real-world scenarios.
  • Question: Who is the intended audience for this book?

    Answer: This book is designed for data scientists, statisticians, and anyone involved in data analysis. It caters to both beginners seeking foundational knowledge as well as experienced professionals needing a refresher on key concepts. By bridging the gap between theory and practice, it serves as an excellent reference for applied data analytics in diverse fields such as business intelligence, academia, and machine learning.
  • Question: How does this book apply statistics to data science?

    Answer: The book applies statistics directly to data science by illustrating how statistical methods can be utilized in data analytics and machine learning. Each concept is paired with practical examples and coding implementation, particularly in Python, making the content actionable. For instance, concepts like regression analysis are demonstrated through real data problems, empowering readers to apply statistical techniques effectively in their projects.
  • Question: Is prior knowledge of statistics required to understand this book?

    Answer: While some familiarity with basic statistics could be beneficial, the book is structured to accommodate readers with varying levels of expertise. It breaks down complex ideas into digestible segments, starting from simpler concepts before tackling more sophisticated topics. This approach makes it suitable for complete beginners as well as practitioners looking to deepen their understanding of statistical applications in data science.
  • Question: Are there exercises or practical examples included?

    Answer: Yes, 'Practical Statistics for Data Scientists' includes numerous exercises and practical examples throughout its chapters. Each concept is illustrated with case studies and coding tasks to foster a hands-on learning experience. These exercises enable readers to apply what they have learned and test their understanding effectively, making it a valuable resource for both self-study and classroom use.
  • Question: What programming languages are used in this book?

    Answer: The primary programming language focus in this book is Python, as it is widely used in the data science community for statistical analysis and machine learning. The book includes Python code snippets and examples, which allow readers to implement statistical techniques directly. This practical programming approach ensures that readers can apply what they learn immediately within their data science projects.
  • Question: How can I implement concepts from the book in my data projects?

    Answer: You can implement concepts from the book by following the provided examples and exercises that relate directly to common data science problems. For instance, after learning about regression analysis, you could apply it to a dataset relevant to your field, such as sales predictions or customer behavior analysis. This hands-on approach lets your projects benefit from statistical insights that enhance decision-making and improves outcomes based on data.
  • Question: What is the unique selling point of this book?

    Answer: The unique selling point of 'Practical Statistics for Data Scientists' is its integration of statistical theory with practical application in data science. It distills complex statistical concepts into accessible language while providing applicable tools and techniques. This synergy makes the book indispensable for readers who want not just to learn statistics but also to apply it effectively within their data science workflows.
  • Question: What is the book's approach to teaching statistical concepts?

    Answer: The book adopts a pragmatic approach to teaching statistical concepts by prioritizing real-world applicability over theoretical depth. It focuses on how statistics can answer crucial data questions and support data-driven decision-making. This method is particularly useful for data scientists who need to quickly grasp concepts and apply them to enhance their data analysis skills effectively.
  • Question: Where can I buy 'Practical Statistics for Data Scientists: 50 Essential Concepts 1st Edition'?

    Answer: You can buy 'Practical Statistics for Data Scientists: 50 Essential Concepts 1st Edition' on Ubuy. Ubuy offers a wide range of books and is a trusted platform for acquiring the latest publications, ensuring you get access to quality materials for your learning and professional growth.

Data Processing Editorial Review

  • ubuy Bahrain

"Practical Statistics for Data Scientists: 50 Essential Concepts" is a book that has received mixed reviews from customers. Some readers find it lacking in depth as it only offers a brief introduction to various topics. However, others have found it to be a great read packed with useful statistics and programming knowledge. The book includes helpful R and Python programs and notebooks that can be easily accessed on Github. The concise nature of the book makes it an excellent resource for those who need a quick stats refresher.

Customer Reviews & Ratings

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Pros

  • Includes great R and Python programs and notebooks that are easy to understand
  • Provides a quick refresher of stats knowledge
  • Relevant for those working in the data/business analyst world

Cons

  • Some feel the book only scratches the surface of each concept

Product Price History

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BHD 27

Order now and get it around Tuesday, June 30

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Only 1 item left in stock.
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Ubuy works hard to protect your security and privacy. Our advanced payment security system ensures confidentiality by encrypting your information during transmission using AES (Advanced Encryption Standards) and SSL (Secure Socket Layer) protocols. Your payment details are 100% secure as we do not share your payment details with third party sellers.

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Features & Benefits

  • Explains how to apply various statistical methods to data science
  • Advice on what's important and what's not
  • Quick reference book, accessible and readable
  • Methods for exploratory data analysis
  • Teaches the principles of experimental design
  • Covers regression for estimating outcomes and detecting anomalies