Introduction to Probabilistic and Statistical Methods with Examples in R

This book is a comprehensive and self-contained introduction to probability and statistics for university students, with accompanying implementations of statistical techniques in R. It covers probability theory, descriptive and inferential statistics, and correlation and linear regression analysis, helping readers develop strong analytical thinking skills essential for analysts and data scientists.

Format: Paperback / softback
Length: 157 pages
Publication date: 23 May 2021
Publisher: Springer Nature Switzerland AG

This book is a remarkable blend of theory and applications, ensuring that it provides a comprehensive and largely self-contained introduction to probability and statistics for university students from diverse faculties. It serves as a valuable resource for those seeking to gain a deep understanding of these subjects while also being accessible to those with limited mathematical backgrounds.

The content is meticulously organized into three distinct parts. The first part delves into the fundamental principles of probability theory, providing a solid foundation for understanding random events and their probabilities. The second part introduces readers to the world of descriptive and inferential statistics, where they learn how to collect, analyze, and interpret data to draw meaningful conclusions. The third part focuses on correlation and linear regression analysis, enabling students to explore the relationships between variables and predict future outcomes.

One of the key strengths of this book is its emphasis on practical applications. Through numerous examples and case studies, readers are guided through the process of applying statistical techniques to real-world problems. This hands-on approach not only enhances their analytical thinking skills but also helps them develop a deeper appreciation for the importance of statistics in various fields.

Moreover, the book is accompanied by comprehensive implementations of some rudimentary statistical techniques in the popular programming language R. This feature not only allows students to practice their skills but also provides them with a valuable tool for data analysis and visualization.

Whether you are a university student pursuing a degree in mathematics, statistics, engineering, or any other field, this book is an essential resource for your academic journey. It strikes a perfect balance between theory and applications, offering a comprehensive and engaging introduction to probability and statistics that will equip you with the skills and knowledge needed to succeed in today's data-driven world.

Weight: 454g
Dimension: 235 x 155 (mm)
ISBN-13: 9783030458010
Edition number: 1st ed. 2020