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Multivariate Methods and Forecasting with IBM® SPSS® Statistics

  • Book
  • © 2017

Overview

Authors:
  1. Abdulkader Aljandali

    1. Accounting, Finance and Economics Department, Regent’s University London, London, United Kingdom

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  • Utilizes the popular and accessible IBM SPSS Statistics software package to teach data analysis for business and finance in a step-by-step approach
  • A comprehensive, in-depth guide—especially relative to the competition
  • Explains the statistical assumptions and rationales underpinning application of the IBM SPSS for Statistics package, instead of simply presenting techniques
  • More than 100 color graphs, screen shots, and figures
  • Includes directed download of the software, IBM SPSS Statistics 24 [current version]
  • Includes supplementary material: sn.pub/extras

Part of the book series: Statistics and Econometrics for Finance (SEFF)

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Table of contents (11 chapters)

  1. Front Matter

    Pages i-xvii
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  2. Forecasting Models

    1. Front Matter

      Pages 1-1
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    2. Multivariate Regression

      • Abdulkader Aljandali
      Pages 3-25

    3. Other Useful Topics in Regression

      • Abdulkader Aljandali
      Pages 27-57

    4. The Box-Jenkins Methodology

      • Abdulkader Aljandali
      Pages 59-79

    5. Exponential Smoothing and Naïve Models

      • Abdulkader Aljandali
      Pages 81-93

  3. Multivariate Methods

    1. Front Matter

      Pages 95-95
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    2. Factor Analysis

      • Abdulkader Aljandali
      Pages 97-106

    3. Discriminant Analysis

      • Abdulkader Aljandali
      Pages 107-116

    4. Multidimension Scaling (MDS)

      • Abdulkader Aljandali
      Pages 117-133

    5. Hierchical Log-linear Analysis

      • Abdulkader Aljandali
      Pages 135-149

  4. Research Methods

    1. Front Matter

      Pages 151-151
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    2. Testing for Dependence

      • Abdulkader Aljandali
      Pages 153-158

    3. Testing for Differences Between Groups

      • Abdulkader Aljandali
      Pages 159-166

    4. Current and Constant Prices

      • Abdulkader Aljandali
      Pages 167-172

  5. Back Matter

    Pages 173-178
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Keywords

About this book

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 suchas Factor Analysis, Discriminant Analysis and Multidimensional Scaling (MDS).

Authors and Affiliations

  • Accounting, Finance and Economics Department, Regent’s University London, London, United Kingdom

    Abdulkader Aljandali

About the author

Abdulkader Aljandali, Ph.D., is Senior Lecturer at Regent’s University London. He currently leads the Business Forecasting and the Quantitative Finance module at Regent’s in addition to acting as a Visiting Professor for various universities across the UK, Germany and Morocco. Dr Aljandali is an established member of the Higher Education Academy (HEA) and an active member of the British Accounting and Finance Association (BAFA).

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