SPSS Statistics has always been the most popular form for statistical processing and data analysis worldwide. It’s the shortened acronym for Statistics Product and Service Support. The IBM SPSS Statistics has an extensive family of powerful statistical applications. It includes Basic, IBM Intermediate, IBM Expertise, IBM Industry and IBM Safeguard.
This is an open source project of IBM for statistical research and data file processing. It contains four variants for IBM mainframe RAC and the mainframe of the IBM WebSphere. With SPSS Statistics users can: – Create survey data files by using the pre-designed templates; – Create multiple types of surveys with various options; – Analyze the results in various ways; – Run various tests on the data file by different types of statistical methods. In addition it also contains support for other languages such as Spanish, French, Italian, German, and more.
This is an introduction to the SPSS Statistics for the social sciences by Anil Shah, professor at University of Michigan. This book provides an in depth look at SPSS Statistics with its main focus on economic and financial data. Although economic data is usually discussed in economic journals and by other professionals, this book emphasizes the wide application of SPSS Statistics for the social sciences and business. The main topics are Gender Income Differences, Concentrated Earnings, Purchasing Manager Role, Job Quality and Job Beliefs and Attitudes, Organizational Behavior and Processes. The book has some excellent case studies and graphical representations of typical results from a wide range of techniques used in the statistical analysis.
This book presents data mining using kruskal-walls and related methods. It then discusses selected methods for applying the statistical method called principal components analysis (PCA). The book also reviews selected alternative methodologies and alternative approaches to estimation, aggregation and correlation. The book concludes with a case study of a sample of three variables that were analyzed using PCA.
This book provides a succinct review of the SPSS Statistics concepts and techniques. It reviews SPSS estimation of variance, time series analysis using kruskal-wallisH and log-linear models, data mining using log-linear models and the kruskal-walls’ concept. It also reviews assumptions, designs for time series analysis and how to fit models using the kruskal-walls’ concept. It then reviews the design of contingency tables and how to fit the data for a variety of specifications. Finally it reviews the assumption of constant information. It concludes by briefly reviewing the methods and data sets for testing and estimating the consistency of the predictions.
The e-course that is available from the publisher and at various online websites is an excellent way for a researcher to familiarize themselves with the statistical concepts and to learn how to use the SPSS Statistics packages and tools. It takes into account important topics that every statistical researcher needs to know and learn to effectively analyze and interpret the data from the statistical tests. It can also help a researcher to become more familiar with a statistical test and how to make an accurate analysis of its results.
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