From Data To Decisions
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| Author | : Stuart A. Klugman |
| Publisher | : John Wiley & Sons |
| Total Pages | : 758 |
| Release | : 2012-01-25 |
| Genre | : Business & Economics |
| ISBN | : 0470391332 |
An update of one of the most trusted books on constructing and analyzing actuarial models Written by three renowned authorities in the actuarial field, Loss Models, Third Edition upholds the reputation for excellence that has made this book required reading for the Society of Actuaries (SOA) and Casualty Actuarial Society (CAS) qualification examinations. This update serves as a complete presentation of statistical methods for measuring risk and building models to measure loss in real-world events. This book maintains an approach to modeling and forecasting that utilizes tools related to risk theory, loss distributions, and survival models. Random variables, basic distributional quantities, the recursive method, and techniques for classifying and creating distributions are also discussed. Both parametric and non-parametric estimation methods are thoroughly covered along with advice for choosing an appropriate model. Features of the Third Edition include: Extended discussion of risk management and risk measures, including Tail-Value-at-Risk (TVaR) New sections on extreme value distributions and their estimation Inclusion of homogeneous, nonhomogeneous, and mixed Poisson processes Expanded coverage of copula models and their estimation Additional treatment of methods for constructing confidence regions when there is more than one parameter The book continues to distinguish itself by providing over 400 exercises that have appeared on previous SOA and CAS examinations. Intriguing examples from the fields of insurance and business are discussed throughout, and all data sets are available on the book's FTP site, along with programs that assist with conducting loss model analysis. Loss Models, Third Edition is an essential resource for students and aspiring actuaries who are preparing to take the SOA and CAS preliminary examinations. It is also a must-have reference for professional actuaries, graduate students in the actuarial field, and anyone who works with loss and risk models in their everyday work. To explore our additional offerings in actuarial exam preparation visit www.wiley.com/go/actuarialexamprep.
| Author | : Raissa Gomez |
| Publisher | : Zee Publishing |
| Total Pages | : 90 |
| Release | : 2024-05-21 |
| Genre | : Computers |
| ISBN | : |
From Data to Decisions: Your Friendly Guide to Understanding Modern Decision Intelligence by Raissa Gomez Feeling overwhelmed by the buzz around "data-driven decisions" and "artificial intelligence"? Don't worry, you're not alone! "From Data to Decisions" is your friendly, jargon-free introduction to the exciting world of Decision Intelligence (DI). No prior experience required! Inside, you'll discover: DI Basics Made Easy: We'll break down the core concepts of DI in simple terms, explaining why it's so important for today's businesses. Real-World Examples, Not Just Theory: Learn how everyday decisions – from choosing a new product to planning a marketing campaign – can be improved with DI. A Roadmap to Getting Started: We'll show you the first steps to take on your DI journey, even if you're starting from scratch. The Future of Decision-Making: Get a sneak peek into how DI is changing the way we work and live. Whether you're a curious student, a business owner, or simply someone who wants to make better decisions, "From Data to Decisions" will give you the confidence and knowledge to embrace this powerful tool. Ready to unlock the secrets of smarter decision-making? Grab your copy of "From Data to Decisions" today and start your DI adventure!
| Author | : Ann E. Watkins |
| Publisher | : John Wiley & Sons |
| Total Pages | : 1705 |
| Release | : 2011 |
| Genre | : Mathematics |
| ISBN | : 0470458518 |
Statistics, 2nd Edition teaches statistics with a modern, data-analytic approach that uses graphing calculators and statistical software. It allows more emphasis to be put on statistical concepts and data analysis rather than following recipes for calculations. This gives readers a more realistic understanding of both the theoretical and practical applications of statistics, giving them the ability to master the subject.
| Author | : Dimitris Bertsimas |
| Publisher | : Ingram |
| Total Pages | : 530 |
| Release | : 2004 |
| Genre | : Business & Economics |
| ISBN | : 9780975914601 |
Combines topics from two traditionally distinct quantitative subjects, probability/statistics and management science/optimization, in a unified treatment of quantitative methods and models for management. Stresses those fundamental concepts that are most important for the practical analysis of management decisions: modeling and evaluating uncertainty explicitly, understanding the dynamic nature of decision-making, using historical data and limited information effectively, simulating complex systems, and allocating scarce resources optimally.
| Author | : Chris J. Lloyd |
| Publisher | : John Wiley & Sons |
| Total Pages | : 512 |
| Release | : 2011-10-25 |
| Genre | : Business & Economics |
| ISBN | : 0470619600 |
A hands-on guide to the use of quantitative methods and software for making successful business decisions The appropriate use of quantitative methods lies at the core of successful decisions made by managers, researchers, and students in the field of business. Providing a framework for the development of sound judgment and the ability to utilize quantitative and qualitative approaches, Data Driven Business Decisions introduces readers to the important role that data plays in understanding business outcomes, addressing four general areas that managers need to know about: data handling and Microsoft Excel, uncertainty, the relationship between inputs and outputs, and complex decisions with trade-offs and uncertainty. Grounded in the author's own classroom approach to business statistics, the book reveals how to use data to understand the drivers of business outcomes, which in turn allows for data-driven business decisions. A basic, non-mathematical foundation in statistics is provided, outlining for readers the tools needed to link data with business decisions; account for uncertainty in the actions of others and in patterns revealed by data; handle data in Excel; translate their analysis into simple business terms; and present results in simple tables and charts. The author discusses key data analytic frameworks, such as decision trees and multiple regression, and also explores additional topics, including: Use of the Excel® functions Solver and Goal Seek Partial correlation and auto-correlation Interactions and proportional variation in regression models Seasonal adjustment and what it reveals Basic portfolio theory as an introduction to correlations Chapters are introduced with case studies that integrate simple ideas into the larger business context, and are followed by further details, raw data, and motivating insights. Algebraic notation is used only when necessary, and throughout the book, the author utilizes real-world examples from diverse areas such as market surveys, finance, economics, and business ethics. Excel® add-ins StatproGo and TreePlan are showcased to demonstrate execution of the techniques, and a related website features extensive programming instructions as well as insights, data sets, and solutions to problems included in the material. Data Driven Business Decisions is an excellent book for MBA quantitative analysis courses or undergraduate general statistics courses. It also serves as a valuable reference for practicing MBAs and practitioners in the fields of statistics, business, and finance.
| Author | : Jerzy Surma |
| Publisher | : Business Expert Press |
| Total Pages | : 161 |
| Release | : 2011-03-06 |
| Genre | : Business & Economics |
| ISBN | : 1606491865 |
This book is about using business intelligence as a management information system for supporting managerial decision making. It concentrates primarily on practical business issues and demonstrates how to apply data warehousing and data analytics to support business decision making. This book progresses through a logical sequence, starting with data model infrastructure, then data preparation, followed by data analysis, integration, knowledge discovery, and finally the actual use of discovered knowledge. All examples are based on the most recent achievements in business intelligence. Finally this book outlines an overview of a methodology that takes into account the complexity of developing applications in an integrated business intelligence environment. This book is written for managers, business consultants, and undergraduate and postgraduates students in business administration.
| Author | : Nate Moore |
| Publisher | : Medical Group Management Association/Center for Research in Ambulatory Health Care Administration |
| Total Pages | : 154 |
| Release | : 2013 |
| Genre | : Medical |
| ISBN | : 9781568294322 |
Data flows into medical practices daily from practice management systems, electronic medical record (EMR) systems, accounting systems and many other sources. Too many practices extract only the bare minimum of data to file claims and meet reporting obligations, without recognizing the value in the flood of data that passes through the practice.
| Author | : Subhashish Samaddar |
| Publisher | : |
| Total Pages | : |
| Release | : 2020-11-21 |
| Genre | : |
| ISBN | : 9780999766965 |
This book is intended for the students and teachers of evidence based decision making, especially when the evidences are obtained from numerical facts. It specifically covers business modeling, decision analytics, and forecasting. All planning and decision making start with some estimation of what the future holds for a business and thus, we need to forecast the future. Generally, there can be more than one forecast for most real situations based on the model one uses to forecast them. Business modeling can help us with calculating what those multiple forecasts of the future mean for the things that the business is interested in, such as profit, costs, pay off, returns etc. These are also called outcomes. Once we get the forecasts depicting the future, we can devise and assess multiple actions, and choose one of them that get the best outcome for the business. Decision analytics help us with this assessment. This book is best used for problem based learning and instruction. Problem based learning introduces the problem first for the students to work on, along with the instructor. Students learn by doing. They can practice multiple problems for practice until the underlying principles and lessons are understood and absorbed. Then the formal theories and principles are presented to make sense of what the students have already done and learned. This can also be called reversed learning because it reverses the process of the traditional learning method of theory first and problem solving later. The first of the book provides the problem and the second half of the book provides brief theories and principles, and solutions of the problems.
| Author | : Peter C. Verhoef |
| Publisher | : Routledge |
| Total Pages | : 339 |
| Release | : 2016-01-08 |
| Genre | : Business & Economics |
| ISBN | : 1317561929 |
Our newly digital world is generating an almost unimaginable amount of data about all of us. Such a vast amount of data is useless without plans and strategies that are designed to cope with its size and complexity, and which enable organisations to leverage the information to create value. This book is a refreshingly practical, yet theoretically sound roadmap to leveraging big data and analytics. Creating Value with Big Data Analytics provides a nuanced view of big data development, arguing that big data in itself is not a revolution but an evolution of the increasing availability of data that has been observed in recent times. Building on the authors’ extensive academic and practical knowledge, this book aims to provide managers and analysts with strategic directions and practical analytical solutions on how to create value from existing and new big data. By tying data and analytics to specific goals and processes for implementation, this is a much-needed book that will be essential reading for students and specialists of data analytics, marketing research, and customer relationship management.
| Author | : Piyanka Jain |
| Publisher | : AMACOM |
| Total Pages | : 276 |
| Release | : 2014-11-05 |
| Genre | : Business & Economics |
| ISBN | : 0814449220 |
There is a misconception in business that the only data that matters is BIG data, and that elaborate tools and data scientists are required to extract any practical information. However, nothing could be further from the truth. If you feel that you can’t understand how to read, let alone implement, these complex software programs that crunch the data and spit out more data, that will no longer be a problem! Authors and analytics experts Piyanka Jain and Puneet Sharma demystify the process of business analytics and demonstrate how professionals at any level can take the information at their disposal and in only five simple steps--using only Excel as a tool--make the decision necessary to increase revenue, decrease costs, improve product, or whatever else is being asked of them at that time. In Behind Every Good Decision, you will learn how to: Clarify the business question Lay out a hypothesis-driven plan Pull relevant data Convert it to insights Make decisions that make an impact Packed with examples and exercises, this refreshingly accessible book explains the four fundamental analytic techniques that can help solve a surprising 80 percent of all business problems. It doesn’t take a numbers person to know that is a formula you need!
