A practical home-buying guide that follows one family through 18 months of bidding wars, rising mortgage rates, failed offers, and hard-earned lessons in Boston's competitive housing market. Drawing on real-world experience, veteran agent Daniel Voss explains inspection waivers, mortgage math, pre-approvals, pricing mistakes, agent selection, and the realities of homeownership after closing. Combining market insights with a compelling narrative, this book offers first-time buyers a realist...

This textbook takes a strategic approach to the broad-reaching subject of experimental design by identifying the objectives behind an experiment and teaching practical considerations that govern design and implementation, concepts that serve as the basis for the analytical techniques covered. Rather than a collection of miscellaneous approaches, chapters build on the planning, running, and analyzing of simple experiments in an approach that results from decades of teaching the subject. In ...

Break free from conventional thinking and master problem solving to confidently navigate high-stakes career decisions. When invisible assumptions and outdated habits dictate your daily routines, you risk following rules no one remembers the reason for. This empowering guide dismantles stale defaults, offering you the clarity needed to conquer complex challenges during your morning commute or focused learning sessions.Stop relying on borrowed opinions and corporate buzzwords to shap...

Break free from conventional thinking and master problem solving to confidently navigate high-stakes career decisions. When invisible assumptions and outdated habits dictate your daily routines, you risk following rules no one remembers the reason for. This empowering guide dismantles stale defaults, offering you the clarity needed to conquer complex challenges during your morning commute or focused learning sessions.Stop relying on borrowed opinions and corporate buzzwords to shap...

Break free from conventional thinking and master problem solving to confidently navigate high-stakes career decisions. When invisible assumptions and outdated habits dictate your daily routines, you risk following rules no one remembers the reason for. This empowering guide dismantles stale defaults, offering you the clarity needed to conquer complex challenges during your morning commute or focused learning sessions.Stop relying on borrowed opinions and corporate buzzwords to shap...

Break free from conventional thinking and master problem solving to confidently navigate high-stakes career decisions. When invisible assumptions and outdated habits dictate your daily routines, you risk following rules no one remembers the reason for. This empowering guide dismantles stale defaults, offering you the clarity needed to conquer complex challenges during your morning commute or focused learning sessions.Stop relying on borrowed opinions and corporate buzzwords to shap...

Break free from conventional thinking and master problem solving to confidently navigate high-stakes career decisions. When invisible assumptions and outdated habits dictate your daily routines, you risk following rules no one remembers the reason for. This empowering guide dismantles stale defaults, offering you the clarity needed to conquer complex challenges during your morning commute or focused learning sessions.Stop relying on borrowed opinions and corporate buzzwords to shap...

An Introduction to Statistical Learning provides an accessible overview of the field of statistical learning, an essential toolset for making sense of the vast and complex data sets that have emerged in fields ranging from biology to finance to marketing to astrophysics in the past twenty years. This book presents some of the most important modeling and prediction techniques, along with relevant applications. Topics include linear regression, classification, resampling met...

Ecological Models and Data in R is the first truly practical introduction to modern statistical methods for ecology. In step-by-step detail, the book teaches ecology graduate students and researchers everything they need to know in order to use maximum likelihood, information-theoretic, and Bayesian techniques to analyze their own data using the programming language R. Drawing on extensive experience teaching these techniques to graduate students in ecology, Benjamin Bolker shows ...

Hugely successful and popular text presenting an extensive and comprehensive guide for all R usersThe R language is recognized as one of the most powerful and flexible statistical software packages, enabling users to apply many statistical techniques that would be impossible without such software to help implement such large data sets. R has become an essential tool for understanding and carrying out research.This edition:Features full colour ...

The field's leading text, now completely updated.Modeling dynamical systems — theory, methodology, and applications.Lennart Ljung's System Identification: Theory for the User is a complete, coherent description of the theory, methodology, and practice of System Identification. This completely revised Second Edition introduces subspace methods, methods that utilize frequency domain data, and general non-linear black box methods, including neural networks and neuro-f...

This is the only book actuaries need to understand generalized linear models (GLMs) for insurance applications. GLMs are used in the insurance industry to support critical decisions. Until now, no text has introduced GLMs in this context or addressed the problems specific to insurance data. Using insurance data sets, this practical, rigorous book treats GLMs, covers all standard exponential family distributions, extends the methodology to correlated data structures, and discusses recent de...