
BOOKS - Guide to Advanced Statistical Analysis in R Advanced data analysis – without ...

Guide to Advanced Statistical Analysis in R Advanced data analysis – without tears
Author: April Liu
Year: 2023
Pages: 250
Format: PDF | EPUB
File size: 10.1 MB
Language: ENG

Year: 2023
Pages: 250
Format: PDF | EPUB
File size: 10.1 MB
Language: ENG

Book Description: This book provides a comprehensive guide to advanced statistical analysis using R, covering topics such as linear regression, time series analysis, and Bayesian statistics. The author emphasizes the importance of understanding the underlying principles of statistical analysis and how to apply them in real-world scenarios. The book is written in an approachable style, making it accessible to readers who may not have a strong background in statistics. The book begins by discussing the importance of statistical analysis in modern society and how it has evolved over time. The author highlights the need to develop a personal paradigm for understanding the technological process of developing modern knowledge, as this will be crucial for the survival of humanity and the unification of people in a warring state. The author argues that by studying and understanding the evolution of technology, we can better prepare ourselves for the challenges that lie ahead. The book then delves into the specifics of statistical analysis, starting with linear regression and its applications in various fields. The author provides clear explanations and examples of how to use R to perform linear regression, including how to interpret the results and assess the assumptions of the model. The book also covers more advanced topics such as time series analysis and Bayesian statistics, providing readers with a solid understanding of these techniques and their applications. Throughout the book, the author emphasizes the importance of critical thinking and skepticism when interpreting statistical results. He encourages readers to question the assumptions of the models and to consider alternative explanations for the data. The book also includes practical exercises and case studies to help readers apply the concepts they have learned to real-world problems.
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