SPSS statistics for data analysis and visualization - McCormick, Keith; Salcedo, Jesus; Peck, Jon; Wheeler, Andrew (Indianapolis, IN : John Wiley & Sons, Inc., 2017)
This book includes the basics of SPSS Statistics to show you advanced techniques that exploit the full capabilities of SPSS. The authors explain when and why to use each technique, and then walk you through the execution with a pragmatic, nuts and bolts example. Coverage includes extensive, in-depth discussion of advanced statistical techniques, data visualization, predictive analytics, and SPSS programming, including automation and integration with other languages like R and Python.
Part I. Advanced statistics -- Comparing and contrasting IBM SPSS AMOS with other multivariate techniques -- Monte Carlo simulation and IBM SPSS bootstrapping -- Regression with categorical outcome variables -- Building hierarchical linear models -- Part II. Data visualization -- Take your data visualizations to the next level -- The code behind SPSS graphics: graphics production language -- Mapping in IBM SPSS statistics -- Geospatial analytics -- Perceptual mapping with correspondence analysis, GPL, and OMS -- Display complex relationships with multidimensional scaling -- Part III. Predictive analysis -- SPSS statistics versus SPSS modeler: can I be a data miner using SPSS statistics? -- IBM SPSS data preparation -- Model complex interactions with IBM SPSS neural networks -- Powerful and intuitive: IBM SPSS decision trees -- Find patterns and make predictions with K nearest neighbors -- Part IV. Syntax, data management, and programmability -- Write more efficient and elegant code with SPSS syntax techniques -- Automate your analyses with SPSS syntax and the output management system -- Statistical extension commands.
Includes index.
Keywords: SPSS (Computer file); SPSS (Computer file); Social sciences -- Statistical methods -- Computer programs; Social sciences -- Statistical methods -- Computer programs