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Sinopsis
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).
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Acerca del autor
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).
De la contraportada
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).
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, screenshots, and figures
Includes directed download of the software, IBM SPSS Statistics 24 [current version]
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 an excellent book for learning SPSS and a long awaited addition for teaching statistics in business and finance studies. The emphasis is on the effective use of SPSS and on correctly applying and interpreting results. A wonderful guide I have found so far.
- Dr Yacine Belghitar - Cranfield University
Dr Aljandali's book fills an important gap in the area of applied economics by making econometric concepts easier to grasp and apply using SPSS software, which makes it an invaluable handbook for students, researchers and practitioners.
- Dr Mete Feridun - University of Cambridge
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Multivariate Methods and Forecasting with IBM® SPSS® Statistics
Publicado por
Springer International Publishing Aug 2018, 2018
ISBN 10: 3319859226
ISBN 13: 9783319859224
Nuevo
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Librería: BuchWeltWeit Ludwig Meier e.K., Bergisch Gladbach, Alemania
Calificación del vendedor: 5 de 5 estrellas
Taschenbuch. Condición: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -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). 196 pp. Englisch. Nº de ref. del artículo: 9783319859224
Cantidad disponible: 2 disponibles
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Multivariate Methods and Forecasting with IBM® SPSS® Statistics
Publicado por
Springer International Publishing, Springer International Publishing, 2018
ISBN 10: 3319859226
ISBN 13: 9783319859224
Nuevo
Taschenbuch
Librería: AHA-BUCH GmbH, Einbeck, Alemania
Calificación del vendedor: 5 de 5 estrellas
Taschenbuch. Condición: Neu. Druck auf Anfrage Neuware - Printed after ordering - 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). Nº de ref. del artículo: 9783319859224
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Multivariate Methods and Forecasting with IBM® SPSS® Statistics (Statistics and Econometrics for Finance)
Librería: Ria Christie Collections, Uxbridge, Reino Unido
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Multivariate Methods and Forecasting with IBM® SPSS® Statistics
Publicado por
Springer International Publishing, 2018
ISBN 10: 3319859226
ISBN 13: 9783319859224
Nuevo
Tapa blanda
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Multivariate Methods and Forecasting with IBM® SPSS® Statistics
Librería: Basi6 International, Irving, TX, Estados Unidos de America
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Condición: Brand New. New. US edition. Expediting shipping for all USA and Europe orders excluding PO Box. Excellent Customer Service. Nº de ref. del artículo: ABEJUNE24-264176
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Multivariate Methods and Forecasting with IBM® SPSS® Statistics
Publicado por
Springer International Publishing, Springer International Publishing Aug 2018, 2018
ISBN 10: 3319859226
ISBN 13: 9783319859224
Nuevo
Taschenbuch
Librería: buchversandmimpf2000, Emtmannsberg, BAYE, Alemania
Calificación del vendedor: 5 de 5 estrellas
Taschenbuch. Condición: Neu. Neuware -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).Springer Verlag GmbH, Tiergartenstr. 17, 69121 Heidelberg 196 pp. Englisch. Nº de ref. del artículo: 9783319859224
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Multivariate Methods and Forecasting with IBM SPSS Statistics
Librería: Chiron Media, Wallingford, Reino Unido
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Multivariate Methods and Forecasting with IBM® SPSS® Statistics (Statistics and Econometrics for Finance)
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Multivariate Methods and Forecasting with IBM? SPSS? Statistics (Statistics and Econometrics for Finance)
Librería: Books Puddle, New York, NY, Estados Unidos de America
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Condición: New. pp. 195. Nº de ref. del artículo: 26380018827
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Multivariate Methods and Forecasting with IBM? SPSS? Statistics (Statistics and Econometrics for Finance)
Impresión bajo demandaLibrería: Majestic Books, Hounslow, Reino Unido
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Condición: New. Print on Demand pp. 195. Nº de ref. del artículo: 382803796
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