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50 Ways to Protect Your Identity and Your CreditEverything You Need to Know About Identity Theft, Credit Cards, Credit Repair, and Credit Reports "The author substitutes straight talk for legal mumbo-jumbo in 50 Ways to Protect Your Identity and Your Credit. Reading this book is like getting a black belt in consumer self-defense."--Jim Bohannon, host of "The Jim Bohannon Show "Identity theft is among the fastest-growing problems facing Americans today. This book will help you learn all you need to know to protect your lives, money, and security. Consider it your first stop in your quest for knowledge and guidance to prevent ID theft." --Robert Powell, Editor of CBS "MarketWatch "As one who has lived through some of the nightmare scenarios discussed by the author, "Detecting and stopping identity thieves is imperative to protecting your finances and financial reputation. Steve Weisman shows you how to protect yourself and what steps to take if you are victimized. This is a must-read for anyone with a bank account and a credit card!"--Bonnie Bleidt, Boston Stock Exchange Reporter, CBS4 Boston, Host of "Early Exchange, WBIX Don?t be a victim! Save your identity, save your credit--and save a fortune! 10,000,000 Americans had their identities stolen last year--don?t be the next! Discover easy steps you can take now to reduce your vulnerability. Recognize "phishing" and other identityscams--online and off. Learn what you must do immediately if you?ve been attacked. Defend yourself against credit rip-offs, and stop paying more than you have to! It?s all here: simple rules, handy checklists, even easy-to-use form letters!(c) Copyright Pearson Education. All rights reserved.

The increasing availability of data in the current information society has led to the need for valid tools for its modelling and analysis. Data mining and applied statistical methods are the appropriate tools to extract knowledge from such data. "Applied Data Mining: Statistical Methods for Business and Industry" provides an accessible introduction to data mining methods in a consistent and application-oriented statistical framework. It describes six case studies, taken from real industry projects, highlighting the current applications of data mining methods.Provides an introduction to data mining methods and applications. Includes coverage of classical and Bayesian multivariate statistical methodology as well as of machine learning and computational data mining methods. Includes many recent developments, such as association and sequence rules, graphical Markov models, memory-based reasoning, credit risk and web mining. Features a number of detailed case studies based on applied projects within industry. Incorporates discussion of data mining software, and the case studies are analysed using SAS and SAS Enterprise Miner. Accessible to anyone with a basic knowledge of statistics or data analysis. Includes an extensive bibliography and pointers to further reading within the text."Applied Data Mining: Statistical Methods for Business and Industry" is primarily aimed at advanced undergraduate and graduate students of data mining, applied statistics, database management, computer science and economics. The case studies give guidance to professionals working in industry on projects involving large volumes of data, such as in customer relationship management, web design, riskmanagement, marketing, economics and finance.