Articoli correlati a Practical Time Series Forecasting: A Hands-on Guide
Sinossi
Practical Time Series Forecasting is a hands-on introduction to quantitative forecasting of time series. Quantitative forecasting is an important component of decision making in a wide range of areas and across many business functions including economic forecasting, workload projections, sales forecasts, and transportation demand. Of course, forecasting is widely used also outside of business, such as in demography and climatology.The book introduces readers to the most popular statistical models and data mining algorithms used in practice. It covers issues relating to different steps of the forecasting process, from goal definition through data visualization, modeling, performance evaluation to model deployment.Practical Time Series Forecasting is suitable for courses on forecasting at the upper-undergraduate and graduate levels. It offers clear explanations, examples, end-of-chapter problems and a case.Methods are illustrated using XLMiner, an Excel add-on. However, any software that has time series forecasting capabilities can be used with the book.Galit Shmueli is Professor of Statistics at the University of Maryland's Smith School of Business. She is co-author of the textbook Data Mining for Business Intelligence, and the book Modeling Online Auctions, among many other publications in professional journals. She has been teaching courses on forecasting and data mining at the University of Maryland, the Indian School of Business, and online at Statistics.com.
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L'autore
Galit Shmueli is SRITNE Chaired Professor of Data Analytics and Associate Professor of Statistics & Information Systems at the Indian School of Business. She is best known for her research and teaching in business analytics, with a focus on statistical and data mining methods for contemporary data and applications in information systems and healthcare. Dr. Shmueli's research has been published in the statistics, management, information systems, and marketing literature. She authors over seventy journal articles, books, textbooks and book chapters, including the popular textbook Data Mining for Business Intelligence and Practical Time Series Forecasting. Dr. Shmueli is an award-winning teacher and speaker on data analytics. She has taught at Carnegie Mellon University, University of Maryland, the Israel Institute of Technology, Statistics.com and the Indian School of Business. Her experience spans business and engineering students and professionals, both online and on-ground. Dr. Shmueli teaches courses on data mining, statistics, forecasting, data visualization, and industrial statistics. For more information, see www.galitshmueli.com
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