Introductory Statistics, 10th edition, is written for a one- or two-semester first course in applied statistics and is intended for students who do not have a strong background in mathematics. The only prerequisite is knowledge of elementary algebra. Known for its realistic examples and exercises, clarity and brevity of presentation, and soundness of pedagogical approach, the book encourages statistical interpretation and literacy regardless of student background.

The book employs a clear and...

When faced with a ’human error’ problem, you may be tempted to ask 'Why didn’t these people watch out better?' Or, 'How can I get my people more engaged in safety?' You might think you can solve your safety problems by telling your people to be more careful, by reprimanding the miscreants, by issuing a new rule or procedure and demanding compliance. These are all expressions of 'The Bad Apple Theory' where you believe your system is basically safe if it were not for those few unreliable...

Poole’s "Linear Algebra: A Modern Introduction, Cengage International Edition", 5th, emphasizes a vectors approach and prepares students to transition from computational to theoretical mathematics. Balancing theory and applications, the conversational writing style combines traditional presentation with student-centered learning. Theoretical, computational, and applied topics are presented in a flexible, integrated way. Stressing geometric understanding before computational techniques, vect...

This book is a self-contained treatment of all the mathematics needed by undergraduate and masters-level students of economics. Building up gently from a very low level, the authors provide a clear, systematic coverage of calculus and matrix algebra. The second half of the book gives a thorough account of probability, optimisation and dynamics.The emphasis throughout is on intuitive argument and problem-solving.

All methods are illustrated by examples, exercises and problems selected from cen...

Research Methods for the Biosciences is the perfect resource for students wishing to develop the crucial skills needed for designing, carrying out, and reporting research, with examples throughout the text drawn from real undergraduate projects.

This book brings the power of modern Bayesian thinking, modeling, and computing to a broad audience. In particular, it is an ideal resource for advanced undergraduate statistics students and practitioners with comparable experience. It empowers readers to weave Bayesian approaches into their everyday practice.