Predictive Behavior


Book Description

This book describes a series of laboratory experiments (with a total of 167 independent subjects) on forecasting behavior. In all experiments, the time series to be forecasted was generated by an abstract econometric model involving two or three artificial exogenous variables. This designprovides an optimal background for rational expectations and least-squares learning. As expected, these hypotheses do not explain observed forecasting behavior satisfactorily. Some phenomena related to this lack of rationality are studied: Concentration on changes rather than levels,underestimation of changes and overvaluation of volatile exogenous variables. Some learning behavior is observed. Finally, some aspects of individual forecasts such as prominence of "round" number, dispersion, etc.,are studied.




Behavioral Predictive Modeling in Economics


Book Description

This book presents both methodological papers on and examples of applying behavioral predictive models to specific economic problems, with a focus on how to take into account people's behavior when making economic predictions. This is an important issue, since traditional economic models assumed that people make wise economic decisions based on a detailed rational analysis of all the relevant aspects. However, in reality – as Nobel Prize-winning research has shown – people have a limited ability to process information and, as a result, their decisions are not always optimal. Discussing the need for prediction-oriented statistical techniques, since many statistical methods currently used in economics focus more on model fitting and do not always lead to good predictions, the book is a valuable resource for researchers and students interested in the latest results and challenges and for practitioners wanting to learn how to use state-of-the-art techniques.




Will Predictive Behavioral Targeting Change Online & Direct Marketing Ways?


Book Description

Inhaltsangabe:Introduction: Over the time, many Internet users have rejected online advertisement. The reason is that users do not associate with the ordinary advertisement and therefore can not find a connection to it. The products and services shown on websites are not what a particular user wants to have, wishes or needs. This capstone should emphasize that through 'Predictive Behavioral Targeted' advertisement the insensitivity will be increased significantly in comparison to ordinary online advertisement while talking about WEB 2.0. Advertisement for specific products will be created and developed just for exact kinds of people and not for the mass. That will sell products much faster and companies or advertisement agencies do not have to place unnecessary spots, banners, etc. on websites anymore. This document will give precise analyzed information and answers to the question if 'Predictive Behavioral Targeting will change Online and Direct Marketing ways in near future'. To understand the principles of online marketing I will explain how traditional online marketing has been established, what kinds of marketing have been used the most, which ones have been most effective, which ones will continue to grow and have a huge impact on our society and its buying patterns. Inhaltsverzeichnis:Table of Contents: 1.Introduction1 1.1Problem Statement1 1.2The Establishment of the Online Advertisement2 2.Standard Banner Sizes3 2.1Effectiveness of Special Banner Implementation5 2.2Development of Banner & Co5 3.Behavior and Reasons for Internet Users6 3.1Behavior Profile7 3.2Internet Usage8 3.3Study of Users in Social Networks8 3.4Registration Behavior9 3.5Activity Level10 3.6Behavior in Changes of Social Networks10 3.7Acceptance of Online Advertisement on Social Networks11 4.Market Share of Online Advertisement11 5.Development through Time11 6.Direct Marketing Overview12 7.Decrease of Transaction Cost13 8.Search Engine Marketing14 8.1Optimization of Search Engine Hit Lists14 8.1.1Page Rank By Google15 8.2Process Optimization16 8.3Popularity16 8.4Product Information16 8.5Company s Information16 8.6Quality of the Content17 8.7Internationality17 8.8Additional Information17 9.Personalization17 10.Payment Methods for Search Engines17 11.Banner Advertisement Definition18 11.1Banner Advertisement Payment Possibilities18 12.E-Mail Marketing Definition18 12.1Different Forms of E-Mail Marketing19 12.2Payment Methods of E-Mail [...]




Predictive Analytics


Book Description

"Mesmerizing & fascinating..." —The Seattle Post-Intelligencer "The Freakonomics of big data." —Stein Kretsinger, founding executive of Advertising.com Award-winning | Used by over 30 universities | Translated into 9 languages An introduction for everyone. In this rich, fascinating — surprisingly accessible — introduction, leading expert Eric Siegel reveals how predictive analytics (aka machine learning) works, and how it affects everyone every day. Rather than a “how to” for hands-on techies, the book serves lay readers and experts alike by covering new case studies and the latest state-of-the-art techniques. Prediction is booming. It reinvents industries and runs the world. Companies, governments, law enforcement, hospitals, and universities are seizing upon the power. These institutions predict whether you're going to click, buy, lie, or die. Why? For good reason: predicting human behavior combats risk, boosts sales, fortifies healthcare, streamlines manufacturing, conquers spam, optimizes social networks, toughens crime fighting, and wins elections. How? Prediction is powered by the world's most potent, flourishing unnatural resource: data. Accumulated in large part as the by-product of routine tasks, data is the unsalted, flavorless residue deposited en masse as organizations churn away. Surprise! This heap of refuse is a gold mine. Big data embodies an extraordinary wealth of experience from which to learn. Predictive analytics (aka machine learning) unleashes the power of data. With this technology, the computer literally learns from data how to predict the future behavior of individuals. Perfect prediction is not possible, but putting odds on the future drives millions of decisions more effectively, determining whom to call, mail, investigate, incarcerate, set up on a date, or medicate. In this lucid, captivating introduction — now in its Revised and Updated edition — former Columbia University professor and Predictive Analytics World founder Eric Siegel reveals the power and perils of prediction: What type of mortgage risk Chase Bank predicted before the recession. Predicting which people will drop out of school, cancel a subscription, or get divorced before they even know it themselves. Why early retirement predicts a shorter life expectancy and vegetarians miss fewer flights. Five reasons why organizations predict death — including one health insurance company. How U.S. Bank and Obama for America calculated the way to most strongly persuade each individual. Why the NSA wants all your data: machine learning supercomputers to fight terrorism. How IBM's Watson computer used predictive modeling to answer questions and beat the human champs on TV's Jeopardy! How companies ascertain untold, private truths — how Target figures out you're pregnant and Hewlett-Packard deduces you're about to quit your job. How judges and parole boards rely on crime-predicting computers to decide how long convicts remain in prison. 182 examples from Airbnb, the BBC, Citibank, ConEd, Facebook, Ford, Google, the IRS, LinkedIn, Match.com, MTV, Netflix, PayPal, Pfizer, Spotify, Uber, UPS, Wikipedia, and more. How does predictive analytics work? This jam-packed book satisfies by demystifying the intriguing science under the hood. For future hands-on practitioners pursuing a career in the field, it sets a strong foundation, delivers the prerequisite knowledge, and whets your appetite for more. A truly omnipresent science, predictive analytics constantly affects our daily lives. Whether you are a consumer of it — or consumed by it — get a handle on the power of Predictive Analytics.




Handbook of Implicit Social Cognition


Book Description

Virtually every question in social psychology is currently being shaped by the concepts and methods of implicit social cognition. This tightly edited volume provides the first comprehensive overview of the field. Foremost authorities synthesize the latest findings on how automatic, implicit, and unconscious cognitive processes influence social judgments and behavior. Cutting-edge theories and data are presented in such crucial areas as attitudes, prejudice and stereotyping, self-esteem, self-concepts, close relationships, and morality. Describing state-of-the-art measurement procedures and research designs, the book discusses promising applications in clinical, forensic, and other real-world contexts. Each chapter both sums up what is known and identifies key directions for future research.




Predictive Evaluation


Book Description

At last, an answer to the question that has bedeviled trainers for decades. Predictive evaluation enables you to effectively and accurately forecast training's value to your company, measure against these predictions, establish indicators to track your progress, make midcourse corrections, and report the results in a language that business executives respond to and understand. Dave Basarab explains how to begin by identifying the specific goals and beliefs you want to instill in participants. The next step is to determine exactly what these will look like when put into action. Finally you develop quantifiable measures of how employees' adopting the target beliefs and goals will impact the business. A key strength of this process is that it is profoundly collaborative—supervisors and employees work together to establish standards for success each step of the way. A how-to guide filled with worksheets, examples, and other tools, Predictive Evaluation ensures that, rather than being regarded as an expense and an act of faith, training will be seen as an investment with a concrete payoff.




Sizing People Up


Book Description

A former FBI agent shares his simple but powerful toolkit for assessing who you can trust--and who you can't. After two decades as a behavior analyst in the FBI, Robin Dreeke knows a thing or two about sizing people up. He's navigated complex situations that range from handling Russian spies to navigating the internal politics at the Bureau. Through that experience, he was forced to develop a knack for reading people--their intentions, their capabilities, their desires and their fears. Dreeke's first book, It's Not All About "Me," has become a cult favorite with readers seeking to build quick rapport with others. His last book, The Code of Trust, was about how to inspire trust in others as a leader. In Sizing People Up, Dreeke shares his simple, six-step system that helps you predict anyone's future behavior based on their words, goals, patterns of action, and the situation at hand. Predicting the behavior of others is an urgent need for anyone whose work involves relationships with others, whether it's leading an organization, collaborating with a teammate, or closing a sale. But predictability is not as simple as good and evil, or truth and fiction. Allies might make a promise with every intention of keeping it, not realizing that they will be unable to do so due to some personal shortcoming. And those seeking to thwart your endeavor may not realize how reliable their malevolent tells have become. Dreeke's system is simple, but powerful. For instance, a colleague might have a strong moral code, but do they believe your relationship will be long-term? Even the most upstanding person can betray your trust if they don't see themselves tied to you or your desired result in the long term. How can you determine whether someone has both the skill and will to do what they've said they're going to do? Behaviors as subtle as how they take notes will reveal their reliability. Using this book as their manual, readers will be able to quickly and easily determine who they can trust and who they can't; who is likely to deliver on promises and who will disappoint; and when a person is vested in your success vs when they are actively plotting your demise. With this knowledge they can confidently embark on anything from a business venture to a romantic relationship to a covert operation without the stress of the unknown.




Predictive Analytics using R


Book Description

This book is about predictive analytics. Yet, each chapter could easily be handled by an entire volume of its own. So one might think of this a survey of predictive modeling. A predictive model is a statistical model or machine learning model used to predict future behavior based on past behavior. In order to use this book, one should have a basic understanding of mathematical statistics - it is an advanced book. Some theoretical foundations are laid out but not proven, but references are provided for additional coverage. Every chapter culminates in an example using R. R is a free software environment for statistical computing and graphics. You may download R, from a preferred CRAN mirror at http: //www.r-project.org/. The book is organized so that statistical models are presented first (hopefully in a logical order), followed by machine learning models, and then applications: uplift modeling and time series. One could use this a textbook with problem solving in R-but there are no "by-hand" exercises.




Predictive Control


Book Description

This book is a comprehensive introduction to model predictive control (MPC), including its basic principles and algorithms, system analysis and design methods, strategy developments and practical applications. The main contents of the book include an overview of the development trajectory and basic principles of MPC, typical MPC algorithms, quantitative analysis of classical MPC systems, design and tuning methods for MPC parameters, constrained multivariable MPC algorithms and online optimization decomposition methods. Readers will then progress to more advanced topics such as nonlinear MPC and its related algorithms, the diversification development of MPC with respect to control structures and optimization strategies, and robust MPC. Finally, applications of MPC and its generalization to optimization-based dynamic problems other than control will be discussed. Systematically introduces fundamental concepts, basic algorithms, and applications of MPC Includes a comprehensive overview of MPC development, emphasizing recent advances and modern approaches Features numerous MPC models and structures, based on rigorous research Based on the best-selling Chinese edition, which is a key text in China Predictive Control: Fundamentals and Developments is written for advanced undergraduate and graduate students and researchers specializing in control technologies. It is also a useful reference for industry professionals, engineers, and technicians specializing in advanced optimization control technology.







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