Management Sciences and Multivariate Analysis: Research Projects, Analysis, and Discussion of Results. Volume I: Dependent Techniques
Keywords:
Administración, Análisis Multivariante, Técnicas DependientesSynopsis
With greater computing capabilities and resource availability nowadays, multivariate analysis is increasingly featured in various software applications, thereby expanding its potential use across disciplines such as Administrative Sciences. The Statistical Package for the Social Sciences (SPSS) by IBM, Analytics, Business Intelligence and Data Management (SAS) by SAS Institute and/or World Programming, Statistica by STATISTICA, and the R language (open-source software) are among the most widely used models in academic and professional fields worldwide. Consequently, it's no surprise that Administrative Sciences support academic development, appearing in various postgraduate programs and in the professional world corresponding to Social Sciences. This trend is leading to a growing presentation of reports, articles, book chapters, or entire books discussing various theoretical-empirical aspects and their interpretation based on such software applications. In our case, we've adopted IBM's SPSS 20 for developing the topics in this book.
Based on the aforementioned, we present the work: "Administrative Sciences and Multivariate Analysis under the Approach of Dependent Techniques. Research Projects, Analysis, and Discussion of Results, Volume I," with a triple purpose:
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To provide a document that serves both those familiar and unfamiliar with the topic, who need to understand the concepts discussed in this volume and manipulate the various commands offered by IBM's SPSS 20 regarding the problem cases presented as examples.
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For a better understanding of case treatment, we present the sequence proposed by Hair et al. (1999) of the six steps: objectives, design, assumptions, execution, interpretation, and validation, as the axis for presenting and resolving these cases.
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As the Coordinator of the Doctorate in Administrative Sciences at the Centro Universitario de Ciencias Económico Administrativas (CUCEA) of the University of Guadalajara (UdG), to present the base book for the course Quantitative Methods I and II.
It is the author's desire to contribute to the reader's acquisition of knowledge applicable in the practical world and aiding in its theoretical interpretation. If not, it is hoped that at least it serves as another useful step towards achieving their academic and/or professional formation.
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References
IBM (2011a). IBM SPSS Statistics Base 20. EUA. .Industrial Business Machines. Recuperado el 20161201 de:
ftp://public.dhe.ibm.com/software/analytics/spss/documentation/statistics/20.0/e
s/client/Manuals/IBM_SPSS_Statistics_Base.pdf
IBM (2011b).Guía breve de IBM SPSS Statistics 20. EUA.Industrial Business Machines. Recuperado el 20161201 de: ftp://public.dhe.ibm.com/software/analytics/spss/documentation/statistics/20.0/e s/client/Manuals/IBM_SPSS_Statistics_Brief_Guide.pdf
IBM (2011c). IBM SPSS Missing Values 20. EUA. .Industrial Business Machines. Recuperado el 20161201 de:
ftp://public.dhe.ibm.com/software/analytics/spss/documentation/statistics/20.0/e s/client/Manuals/IBM_SPSS_Missing_Values.pdf
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Published
June 30, 2017
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Copyright (c) 2017 Juan Mejía-Trejo
License
This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License.
Details about this monograph
ISBN-13 (15)
978-607-742-773-5
doi
10.55965/abib.9786077427735.2017a
