Description
Book Synopsis: 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.
Details
Looking to take your data analysis skills to the next level? Look no further than Practical Statistics for Data Scientists: 50+ Essential Concepts Using R and Python. This comprehensive guide is designed for both beginners and experienced data scientists, providing a valuable resource for anyone looking to enhance their statistical analysis capabilities.
Why choose Practical Statistics for Data Scientists? Unlike other statistics books, this one is tailored specifically for those working with real-world data. With over 50 essential concepts, you'll gain a deep understanding of fundamental statistical techniques and how to apply them using popular programming languages like R and Python.
Don't let complex statistical concepts intimidate you. Practical Statistics for Data Scientists breaks down each concept into clear, easy-to-understand explanations, accompanied by real-world examples and practical exercises. Whether you're a data science enthusiast or a professional, this book will become your go-to reference for confidently tackling statistical analyses.
Ready to take your data analysis skills to new heights? Don't miss out on the opportunity to get your hands on Practical Statistics for Data Scientists: 50+ Essential Concepts Using R and Python. Order now and unlock the knowledge and techniques that will set you apart in the competitive field of data science.
Order Practical Statistics for Data Scientists today and embark on your journey towards mastery of statistical analysis!
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