Practical time series forecasting: a hands-on guide (Record no. 180201)

000 -LEADER
fixed length control field 02444 a2200205 4500
008 - FIXED-LENGTH DATA ELEMENTS--GENERAL INFORMATION
fixed length control field 140323b2012 xxu||||| |||| 00| 0 eng d
020 ## - INTERNATIONAL STANDARD BOOK NUMBER
International Standard Book Number 9781468053456
082 ## - DEWEY DECIMAL CLASSIFICATION NUMBER
Classification number 519.55
Item number S4P7
100 ## - MAIN ENTRY--PERSONAL NAME
Personal name Shmueli, Galit
9 (RLIN) 325983
245 ## - TITLE STATEMENT
Title Practical time series forecasting: a hands-on guide
250 ## - EDITION STATEMENT
Edition statement 2nd ed.
260 ## - PUBLICATION, DISTRIBUTION, ETC. (IMPRINT)
Place of publication, distribution, etc United States of America
Name of publisher, distributor, etc Create Space Independent Publishing
Date of publication, distribution, etc 2012
300 ## - PHYSICAL DESCRIPTION
Extent 202 p.
365 ## - TRADE PRICE
Price type code INR
Price amount 935.00
520 ## - SUMMARY, ETC.
Summary, etc 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. Forecasting is also 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 collection, visualization, pre-processing, modeling, performance evaluation to implementation and communication.

The second edition offers a large amount of new content and improved organization. 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 the SRITNE Chaired Professor of Data Analytics at the Indian School of Business. She is co-author of the textbook Data Mining for Business Intelligence and the book Modeling Online Auctions, among several other books and many publications in professional journals. She has been teaching courses on forecasting, data mining and other data analytics topics at the Indian School of Business, University of Maryland’s Smith School of Business, and online at Statistics.com.

(http://www.goodreads.com/book/show/19249671-practical-time-series-forecasting?from_search=true&search_version=service)
650 ## - SUBJECT ADDED ENTRY--TOPICAL TERM
Topical term or geographic name as entry element Time - series analysis - forecasting
9 (RLIN) 251879
650 ## - SUBJECT ADDED ENTRY--TOPICAL TERM
Topical term or geographic name as entry element Statistical methods
9 (RLIN) 18522
650 ## - SUBJECT ADDED ENTRY--TOPICAL TERM
Topical term or geographic name as entry element Data mining
9 (RLIN) 56428
942 ## - ADDED ENTRY ELEMENTS (KOHA)
Item type Books
Source of classification or shelving scheme
Holdings
Withdrawn status Lost status Damaged status Not for loan Collection code Permanent location Current location Shelving location Date acquired Source of acquisition Cost, normal purchase price Item location Total Checkouts Total Renewals Full call number Barcode Date last seen Date last borrowed Copy number Cost, replacement price Koha item type Source of classification or shelving scheme
        Non-fiction Vikram Sarabhai Library Vikram Sarabhai Library   2013-11-28 22 934.96 Slot 1678 (2 Floor, East Wing) 2 3 519.55 S4P7-1 180366 2017-06-01 2015-12-29 1 1885.00 Books  
        Non-fiction Vikram Sarabhai Library Vikram Sarabhai Library   2015-12-30 Amazon.in 1938.12 Slot 1678 (2 Floor, East Wing) 4 4 519.55 S4P7-2 190766 2018-08-28 2018-08-21 2 2084.00 Books  

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