Mathematics Applications and Interpretation for the IB Diploma Higher Level provides comprehensive coverage of the new curriculum, developed for first examinations in 2021. Written by a highly experienced IB author team, this book includes the following features: integrated GeoGebra applets created specifically for the course, worked examples to help you tackle questions and apply concepts and skills, practice questions to help you prepare for the exam, a rich and wide-ranging Theory of Knowledge chapter, and guidance on the Internal Assessment.

First published in 1963, Advances in Parasitology contains comprehensive and up-to-date reviews in all areas of interest in contemporary parasitology. Advances in Parasitology includes medical studies of parasites of major influence, such as Plasmodium falciparum and trypanosomes. The series also contains reviews of more traditional areas, such as zoology, taxonomy, and life history, which shape current thinking and applications. The 2013 impact factor is 4.36.

The study of ecological systems is often impeded by components that escape perfect observation, such as the trajectories of moving animals or the status of plant seed banks. These hidden components can be efficiently handled with statistical modeling by using hidden variables, which are often called latent variables. Notably, the hidden variables framework enables us to model an underlying interaction structure between variables (including random effects in regression models) and perform data clustering, which are useful tools in the analysis of ecological data. This book provides an introduction to hidden variables in ecology, through recent works on statistical modeling as well as on estimation in models with latent variables. All models are illustrated with ecological examples involving different types of latent variables at different scales of organization, from individuals to ecosystems. Readers have access to the data and R codes to facilitate understanding of the model and to adapt inference tools to their own data.

Containing case studies and examples, the book aims to cover extensive research particularly on surface stress and topics related to the variational approach to the subject, and non-standard topics such as the rigorous treatment of constraints and a full discussion of algebraic inequalities associated with realistic material behaviour, and their implications. Serving as an introduction to the basic elements of Finite Elasticity, this textbook is the cornerstone for any graduate-level on the topic, while also providing a template for a host of theories in Solid Mechanics.

Probability for Data Scientists provides students with a mathematically sound yet accessible introduction to the theory and applications of probability. Students learn how probability theory supports statistics, data science, and machine learning theory by enabling scientists to move beyond mere descriptions of data to inferences about specific populations. The book is divided into two parts. Part I introduces readers to fundamental definitions, theorems, and methods within the context of discrete sample spaces. It addresses the origin of the mathematical study of probability, main concepts in modern probability theory, univariate and bivariate discrete probability models, and the multinomial distribution. Part II builds upon the knowledge imparted in Part I to present students with corresponding ideas in the context of continuous sample spaces. It examines models for single and multiple continuous random variables and the application of probability theorems in statistics. Probability for Data Scientists effectively introduces students to key concepts in probability and demonstrates how a small set of methodologies can be applied to a plethora of contextually unrelated problems. It is well suited for courses in statistics, data science, machine learning theory, or any course with an emphasis in probability. Numerous exercises, some of which provide R software code to conduct experiments that illustrate the laws of probability, are provided in each chapter.

Support English language skills while improving subject content knowledge with a comprehensive three-level lower secondary programme specifically designed for non-native English speaking students studying Mathematics through the medium of English. - Benefit from a flexible programme that ensures thorough preparation for the IGCSE and equivalent courses and is suitable as a stand-alone course. - Engage interest with clear text, stimulating exercises and numerous worked examples. Reinforce the material taught within each lesson with the accompanying Workbook, providing extra practice and homework activities. Make the most of the series with the Teacher's Guide containing answers to the Coursebook and Workbook exercises, guidance on delivering lessons and methodological support.