Multivariate Methods and Forecasting with IBM (R) SPSS (R) Statistics (Paperback, Softcover reprint of the original 1st ed. 2017)

This is the second of a two-part guide to quantitative analysis using the IBM SPSS Statistics software package; this volume focuses on multivariate statistical methods and advanced forecasting techniques. More often than not, regression models involve more than one independent variable. For example, forecasting methods are commonly applied to aggregates such as inflation rates, unemployment, exchange rates, etc., that have complex relationships with determining variables. This book introduces multivariate regression models and provides examples to help understand theory underpinning the model. The book presents the fundamentals of multivariate regression and then moves on to examine several related techniques that have application in business-orientated fields such as logistic and multinomial regression. Forecasting tools such as the Box-Jenkins approach to time series modeling are introduced, as well as exponential smoothing and naive techniques. This part also covers hot topics such as Factor Analysis, Discriminant Analysis and Multidimensional Scaling (MDS).

General

Imprint:	Springer International Publishing AG
Country of origin:	Switzerland
Series:	Statistics and Econometrics for Finance
Release date:	August 2018
First published:	2017
Authors:	Abdulkader Aljandali
Dimensions:	235 x 155 x 11mm (L x W x T)
Format:	Paperback
Pages:	178
Edition:	Softcover reprint of the original 1st ed. 2017
ISBN-13:	978-3-319-85922-4
Categories:	Books > Science & Mathematics > Mathematics > Probability & statistics Books > Business & Economics > Finance & accounting > Finance > Corporate finance Books > Business & Economics > Business & management > Business mathematics & systems > General Books > Money & Finance > Corporate finance
LSN:	3-319-85922-6
Barcode:	9783319859224

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