SPSS Programming and Data Management, 4th Edition: A Guide for ...

OverviewChapter1This book is divided into two main sections:• Data management using the SPSS command language. Although many of these taskscan also be performed with the menus and dialogboxes,someverypowerfulfeatures are available only with command syntax.• Programming with SPSS and Python. The SPSS Python plug-in provides the abilityto integrate the capabilities of the Python programming language with SPSS.Oneofthemajorbenefits of Python is the ability to add jobwise flow controlto the SPSS command stream. SPSS can execute casewise conditional actionsbased on criteria that evaluate each case, but jobwise flow control—such asrunning different procedures for different variables based on data type or level ofmeasurement, or determining which procedure to run next based on the resultsof the last procedure—is much more difficult. The SPSS Python plug-in makesjobwise flow control much easier to accomplish.For readers who may be more familiar with the commands in the SAS system, Chapter22 provides examples that demonstrate how some common data management andprogramming tasks are handled in both SAS and SPSS.Using This BookThis book is intended for use with SPSS release 15.0. or later. Many examples willwork with earlier versions, but some commands and features are not available in earlierreleases. Some of the Python examples require SPSS 15.0.1.Most of the examples shown in this book are designed as hands-on exercises thatyou can perform yourself. The CD that comes with the book contains the commandfiles and data files used in the examples. All of the sample files are contained in theexamples folder.• \examples\commands contains SPSS command syntax files.1