Multivariate Methods and Forecasting with IBM® SPSS® Statistics

Multivariate Methods and Forecasting with IBM® SPSS® Statistics
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Artikel-Nr:
9783319564807
Veröffentl:
2017
Einband:
HC runder Rücken kaschiert
Erscheinungsdatum:
14.07.2017
Seiten:
196
Autor:
Abdulkader Aljandali
Gewicht:
465 g
Format:
241x160x17 mm
Serie:
Statistics and Econometrics for Finance
Sprache:
Englisch
Beschreibung:

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).
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).
Utilizes the popular and accessible IBM SPSS Statistics software package to teach data analysis for business and finance in a step-by-step approach
1 Multivariate Regression.- 2 Other Useful Topics in Regression.- 3 The Box-Jenkins Methodology.- 4 Exponential Smoothing and Naïve Models.- 5 Factor Analysis.- 6 Discriminant Analysis.- 7 Multidimensional Scaling.- 8 Hierarchical Log-Linear Analysis.- 9 Testing for Independence.- 10 Testing for Differences Between Groups.- 11 Current and Constant Prices.

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