Название: Applied Statistics with Python Volume I: Introductory Statistics and Regression
Автор: Leon Kaganovskiy
Издательство: CRC Press
Год: 2025
Страниц: 320
Язык: английский
Формат: pdf (true), epub
Размер: 16.6 MB

Applied Statistics with Python: Volume I: Introductory Statistics and Regression concentrates on applied and computational aspects of statistics, focusing on conceptual understanding and Python-based calculations. Based on years of experience teaching introductory and intermediate Statistics courses at Touro University and Brooklyn College, this book compiles multiple aspects of applied statistics, teaching the reader useful skills in statistics and computational science with a focus on conceptual understanding. This book does not require previous experience with statistics and Python, explaining the basic concepts before developing them into more advanced methods from scratch. Applied Statistics with Python is intended for undergraduate students in business, economics, biology, social sciences, and natural science, while also being useful as a supplementary text for more advanced students.

Key Features:
• Concentrates on more introductory topics such as descriptive statistics, probability, probability distributions, proportion and means hypothesis testing, as well as one-variable regression.
• The book’s computational (Python) approach allows us to study Statistics much more effectively. It removes the tedium of hand/calculator computations and enables one to study more advanced topics.
• Standardized sklearn Python package gives efficient access to machine learning topics.
• Randomized homework as well as exams are provided in the author’s course shell on My Open Math web portal (free).

In this book, I don't assume previous experience in Statistics. We learn the basic concepts and develop more advanced methods from scratch. I use Python as a computational tool at every step because of its amazing versatility and flexibility. It is a free programming language that is used by beginners and advanced practitioners alike with many free add-on libraries for Statistics and its applications. It is a scripting language that allows turning otherwise tedious hand calculations into step-by-step functions where students can see the results of every computation to obtain information from the data in real-time.

The main difference between this textbook and others is weaving code into the text at every step in a clear and accessible way to give students a hands-on computational tool that can benefit them in this and many other courses. The homework for each chapter and exams are provided in my course shell on My Open Math web portal. It is an amazing free platform to teach Mathematics and Statistics. All problems are randomized. I provide scripting files for each chapter with clear instructions for each problem, and students have remarked that they liked the course a lot compared to their peers who had to deal with old-style approaches to Statistics.






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