Multivariate Methods and Forecasting with IBM SPSS Statistics

Download or Read online Multivariate Methods and Forecasting with IBM SPSS Statistics full in PDF, ePub and kindle. This book written by Abdulkader Aljandali and published by Springer which was released on 06 July 2017 with total pages 178. We cannot guarantee that Multivariate Methods and Forecasting with IBM SPSS Statistics book is available in the library, click Get Book button to download or read online books. Join over 650.000 happy Readers and READ as many books as you like.

Multivariate Methods and Forecasting with IBM   SPSS   Statistics
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Publisher : Springer
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ISBN : 9783319564814
Pages : 178 pages
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Download or Read Online Multivariate Methods and Forecasting with IBM SPSS Statistics in PDF, Epub and Kindle

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 naïve techniques. This part also covers hot topics such as Factor Analysis, Discriminant Analysis and Multidimensional Scaling (MDS).

Multivariate Methods and Forecasting with IBM   SPSS   Statistics

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

GET BOOK!
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