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This interdisciplinary textbook provides a practical introduction to basic mathematical modelling methodology and analysis. It covers a variety of biological applications and uses these topics in turn to highlight key components in the art of modelling.
This advanced textbook explores small area estimation techniques, covers the underlying mathematical and statistical theory and offers hands-on support with their implementation.
This book presents PLS-SEM as a useful practical statistical toolbox that can be used for estimating many different types of... Læs mere
In biostatistical research and courses, practitioners and students often lack a thorough understanding of how to apply statistical methods to synthesize biomedical... Læs mere
Statistics and Data Visualisation with Python aims to build statistical knowledge from the ground up by enabling the reader to understand the ideas behind... Læs mere
This book is a timely and critical introduction for people who are interested in what data science is (and isn’t), and how it should be applied. The language is conversational and the content is accessible for readers without a quantitative or computational background.
The modern world is awash with data. The R Project is a statistical environment and programming language that can help to make sense of it all. This clear and methodical book will help you learn how to use R from the ground up, giving you a start in the world of data science.
Introduction to Time Series Modeling: with Applications in R, Second Edition covers numerous stationary and... Læs mere
How to apply spatial models using R to a wide range of data used in political science. Models are similar to multidimensional scaling models long used in... Læs mere
This book introduces artificial neural networks to students and professionals. It covers the theory and applications in statistical learning methods with concrete Python code examples.
This accessible guide walks you through the math necessary to thrive in the AI field such as focusing on... Læs mere