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Applied Wavelet Analysis with S-PLUS
Using a visual data analysis approach, wavelet concepts are explained in a way that is intuitive and easy to understand. Furthermore, in addition to wavelets, a whole range of related signal processing techniques such as wavelet packets, local cosine analysis, and matching pursuits are covered, and applications of wavelet analysis are illustrated -including nonparametric function estimation, digital image compression, and time-frequency signal analysis. This book and software package is intended for a broad range of data analysts, scientists, and engineers. While most textbooks on the subject presuppose advanced training in mathematics, this book merely requires that readers be familiar with calculus and linear algebra at the undergraduate level.
A Practical Approach to Landlord and Tenant
Now in its sixth edition, A Practical Approach to Landlord and Tenant continues to provide a comprehensive and systematic guide to the principles and practice of landlord and tenant law. Containing coverage of up to date cases, as well as key documents, this book provides a valuable introduction for students and professionals alike.
The Handbook of Drugs and Society
This handbook provides a comprehensive examination of the past and present roles of drugs in society with a focus on theory, research, policy, and practice. Includes 28 original chapters with multi-disciplinary and international perspectives by top social and behavioral scientists Reviews current knowledge in the field, including key research findings, theoretical developments, and methodological debates Identifies ongoing controversies in the field, emergent topics, and areas in need of further inquiry Discusses individual drugs as well as topics like physiological theories of drug use and abuse, public health implications of drugs, patterns of drugs and crime, international drug trade and trafficking, and designer drugs
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Practical Statistics for Data Scientists
Statistical methods are a key part of of data science, yet very few data scientists have any formal statistics training. Courses and books on basic statistics rarely cover the topic from a data science perspective. This practical guide explains how to apply various statistical methods to data science, tells you how to avoid their misuse, and gives you advice on what's important and what's not. Many data science resources incorporate statistical methods but lack a deeper statistical perspective. If you’re familiar with the R programming language, and have some exposure to statistics, this quick reference bridges the gap in an accessible, readable format. With this book, you’ll learn: Why ...
