Chapter 1 explores the link between the research process and theory and the role of statistics in scientific discovery. Discrete and continuous variables, the building blocks of methodology, take center stage, with clear and elaborate examples and their applicability to scales of measurement and measures of central tendency. Understanding statistics allows us to become better consumers of science and make better judgments and decisions about claims and facts allegedly supported by statistical results.

Channel coding lies at the heart of digital communication and data storage. Fully updated to include current innovations in the field, including a new chapter on polar codes, this detailed introduction describes the core theory of channel coding, decoding algorithms, implementation details, and performance analyses. This edition includes over 50 new end-of-chapter problems to challenge students and numerous new figures and examples throughout.

The authors emphasize a practical approach and clearly present information on modern channel codes, including polar, turbo, and low-density parity-check (LDPC) codes, as well as detailed coverage of BCH codes, Reed–Solomon codes, convolutional codes, finite geometry codes, and product codes for error correction, providing a one-stop resource for both classical and modern coding techniques.

Assuming no prior knowledge in the field of channel coding, the opening chapters begin with basic theory to introduce newcomers to the subject. Later chapters then begin with classical codes, continue with modern codes, and extend to advanced topics such as code ensemble performance analyses and algebraic LDPC code design.

• 300 varied and stimulating end-of-chapter problems test and enhance learning, making this an essential resource for students and practitioners alike.

• Provides a one-stop resource for both classical and modern coding techniques.

• Starts with the basic theory before moving on to advanced topics, making it perfect for newcomers to the field of channel coding.

• 180 worked examples guide students through the practical application of the theory.

Explore the fundamentals of biomedical engineering technologies with this thought-provoking introduction, framed around modern-day global cancer inequities. Connecting engineering principles to real-world global health scenarios, this textbook introduces major technological advances in cancer care through the lens of global health inequity, discusses how promising new technologies can address this inequity, and demonstrates how novel medical technologies are adopted for real-world clinical use. It includes modular chapters designed to enable a flexible pathway through the material for students from a wide range of backgrounds; boxed discussion of contemporary issues in engineering for global health, encouraging students to explore ethical questions related to science and society; supplementary lab modules for hands-on experience in translating engineering principles into healthcare solutions; and over 200 end-of-chapter problems targeting multiple learning outcomes to solidify student understanding. Designed to equip students with all the critical, technical, and ethical knowledge they need to excel, this is the ideal introduction for students in biomedical engineering and global health.

This chapter provides the tools to compute catastrophe (CAT) risk, which represents a compound measure of the likelihood and magnitude of adverse consequences affecting structures, individuals, and valuable assets. The process consists of first establishing an inventory of assets (here real or simulated) exposed to potential hazards (exposure module). Estimating the expected damage resulting from a given hazard load (according to Chapter 2) is the second crucial step in the assessment process (vulnerability module). The application of damage functions to exposure data forms the basis for calculating loss estimates (loss module). To ensure consistency across perils, the mean damage ratio is used as the main measure for damage footprints D(x,y), with the final loss footprints simply expressed as L(x,y) = D(x,y) × ν(x,y), where ν(x,y) represents the exposure footprint. Damage functions are provided for various hazard loads: blasts (explosions and asteroid impacts), earthquakes, floods, hail, landslides, volcanic eruptions, and wind.

This chapter goes beyond the description of individual events by covering extremes caused by a combination of multiple events. Two main types of interactions are covered: domino effects and compound events. Domino effects, which represent one-way chains of events, are quantified using Markov theory and graph theory. Compound events, which include complex feedback loops in the complex Earth system, are modelled with system dynamics (as in Chapter 4). Two such systems are provided, the ESCIMO climate model and the World2 model of world dynamics. The impact of global warming, pollution, and resource depletion on catastrophes is investigated, as far as ecosystem and societal collapse. The types of catastrophes considered in this chapter are as follows: storm clustering, earthquake clustering (with accelerated fatigue of structures), domino effects at refineries (explosions, fires, toxic spills), cascading failures in physical networks (more precisely blackouts in a power grid), rainforest dieback, lake eutrophication, and hypothetical human population collapse.