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Applied Statistics with Python Volume I Introductory Statistics and Regression - Leon Kaganovskiy 2025 PDF | EPUB CRC Press BOOKS
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Applied Statistics with Python Volume I Introductory Statistics and Regression
Author: Leon Kaganovskiy
Year: 2025
Pages: 320
Format: PDF | EPUB
File size: 16.6 MB
Language: ENG



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W. Powers. Book Description: Applied Statistics with Python Volume I Introductory Statistics and Regression by David M. W. Powers is a comprehensive guide that provides an introduction to statistics and regression analysis using Python programming language. The book covers the fundamental concepts of probability, statistical inference, and regression analysis, providing readers with a solid foundation in statistical thinking and practical skills in data analysis. It is designed for students, researchers, and practitioners who want to learn how to apply statistical methods to real-world problems using Python. The book begins with an overview of the history of statistics and its importance in understanding the world around us. It then delves into the basics of probability, including probability distributions, Bayes' theorem, and random variables. The next chapter covers statistical inference, including confidence intervals and hypothesis testing, which are essential tools for making inferences about populations based on samples. The book also introduces readers to linear regression analysis, including simple and multiple regression, and provides practical examples of how to implement these techniques using Python. Throughout the book, Powers emphasizes the importance of understanding the underlying assumptions of statistical methods and how to interpret results critically. He also stresses the need for reproducibility in scientific research and demonstrates how to document and report statistical analyses using Python. The book concludes with a discussion of the future of statistics and its role in shaping our understanding of the world. Why Study Statistics and Regression? Studying statistics and regression is crucial for understanding the technological process of developing modern knowledge. As technology continues to evolve at an unprecedented pace, it is essential to develop a personal paradigm for perceiving this process. By doing so, we can better understand the impact of technology on society and the potential consequences of our actions.
У. Пауэрс. Applied Statistics with Python Volume I Introductory Statistics and Regression by David M. W. Powers - всеобъемлющее руководство, предоставляющее введение в статистику и регрессионный анализ с использованием языка программирования Python. Книга охватывает фундаментальные понятия вероятности, статистического вывода и регрессионного анализа, предоставляя читателям прочную основу в статистическом мышлении и практические навыки анализа данных. Он предназначен для студентов, исследователей и практиков, которые хотят научиться применять статистические методы к реальным проблемам с помощью Python. Книга начинается с обзора истории статистики и ее важности в понимании окружающего мира. Затем он углубляется в основы вероятности, включая распределения вероятностей, теорему Байеса и случайные величины. Следующая глава охватывает статистический вывод, включая доверительные интервалы и проверку гипотез, которые являются важными инструментами для вынесения выводов о популяциях на основе выборок. Книга также знакомит читателей с линейным регрессионным анализом, включая простую и множественную регрессию, и предоставляет практические примеры того, как реализовать эти техники с помощью Python. На протяжении всей книги Пауэрс подчеркивает важность понимания основных предположений статистических методов и того, как критически интерпретировать результаты. Он также подчеркивает необходимость воспроизводимости в научных исследованиях и демонстрирует, как документировать и сообщать статистический анализ с использованием Python. Книга завершается обсуждением будущего статистики и ее роли в формировании нашего понимания мира. Зачем изучать статистику и регрессию? Изучение статистики и регрессии имеет решающее значение для понимания технологического процесса развития современных знаний. Поскольку технологии продолжают развиваться беспрецедентными темпами, важно разработать личную парадигму восприятия этого процесса. Тем самым мы сможем лучше понять влияние технологий на общество и потенциальные последствия наших действий.
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