2007. SPSS Inc., — 594 p.Experienced data analysts know that a successful analysis or meaningful report often requires more work in acquiring, merging, and transforming data than in specifying the analysis or report itself. SPSS Statistics contains powerful tools for accomplishing and automating these tasks. While much of this capability is available through the graphical user interface, many of the most powerful features are available only through command syntax—and you can make the programming features of its command syntax significantly more powerful by adding the ability to combine it with a full-featured programming language. This book offers many examples of the kinds of things that you can accomplish using command syntax by itself and in combination with other programming language.Contents:
Overview
Data Management
Best Practices and Efficiency Tips
Getting Data into SPSS Statistics
File Operations
Variable and File Properties
Data Transformations
Cleaning and Validating Data
Conditional Processing, Looping, and Repeating
Exporting Data and Results
Scoring Data with Predictive Models
Programming with Python
Introduction
Getting Started with Python Programming in SPSS Statistics
Best Practices
Working with Dictionary Information
Working with Case Data in the Active Dataset
Creating and Accessing Multiple Datasets
Retrieving Output from Syntax Commands
Creating Procedures
Data Transformations
Modifying and Exporting Output Items
Tips on Migrating Command Syntax and Macro Jobs to Python
Special Topics
Programming with R
Introduction
Getting Started with R Program Blocks
Retrieving Variable Dictionary Information
Reading Case Data from SPSS Statistics
Writing Results to a New SPSS Statistics Dataset
Creating Pivot Table Output
Displaying Graphical Output from R
Retrieving Output from Syntax Commands
Extension Commands
SPSS Statistics for SAS ProgrammersIndex
