Description
Featuring improved organization and new material, the Second Edition also includes:
- Popular forecasting methods including smoothing algorithms, regression models, and neural networks
- A practical approach to evaluating the performance of forecasting solutions
- A business-analytics exposition focused on linking time-series forecasting to business goals
- Guided cases for integrating the acquired knowledge using real data
- End-of-chapter problems to facilitate active learning
- A companion site with data sets, R code, learning resources, and instructor materials (solutions to exercises, case studies)Globally-available textbook, available in both softcover and Kindle formats
Author: Kenneth C. Lichtendahl Jr., Galit Shmueli
Publisher: Axelrod Schnall Publishers
Published: 07/19/2016
Pages: 234
Binding Type: Paperback
Weight: 0.91lbs
Size: 10.00h x 7.01w x 0.49d
ISBN13: 9780997847918
ISBN10: 0997847913
BISAC Categories:
- Business & Economics | Forecasting
About the Author
GALIT SHMUELI is Distinguished Professor at the Institute of Service Science, National Tsing Hua University, Taiwan. She is co-author of the best-selling textbook Data Mining for Business Intelligence, among other books and numerous publications in top journals. She has designed and instructed courses on forecasting, data mining, statistics and other data analytics topics at University of Maryland's Smith School of Business, the Indian School of Business, National Tsing Hua University and online at Statistics.com.
KENNETH C. LICHTENDAHL JR. is an Associate Professor of Business Administration at the University of Virginia's Darden School of Business. He specializes in teaching data science to MBA students with R. He was recognized by The Case Centre as its 2015 Outstanding Case Teacher for his course Data Science in Business. His research focuses broadly on making, evaluating, and combining forecasts and has been published in leading academic journals such as Management Science. For more information, visit galitshmueli.com
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