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  • Open Daily: 10am - 10pm
    Alley-side Pickup: 10am - 7pm

    3038 Hennepin Ave Minneapolis, MN
    612-822-4611

Open Daily: 10am - 10pm | Alley-side Pickup: 10am - 7pm
3038 Hennepin Ave Minneapolis, MN
612-822-4611
Multivariate Methods and Forecasting with Ibm(r) Spss(r) Statistics

Multivariate Methods and Forecasting with Ibm(r) Spss(r) Statistics

Aljandali, Abdulkader

Hardcover

Series: Statistics and Econometrics for Finance

Business GeneralProbability & Statistics

ISBN10: 3319564803
ISBN13: 9783319564807
Publisher: Springer Nature
Published: Jul 14 2017
Pages: 178
Weight: 1.00
Height: 0.50 Width: 6.14 Depth: 9.21
Language: English
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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