SPSS Quick Reference

SPSS Quick Reference is a working desk reference, not a course. It assumes you already know what a mean and a standard deviation are, and gets straight to the SPSS command syntax you need to load a dataset, shape it, run the command that answers your question, and reproduce the result six months later.

Ten chapters build from the Syntax Editor and SPSS's keyword/subcommand/period command grammar through variable types, measurement levels, and value labels, transforming data with COMPUTE, IF, and control structures, reading and writing every common file format, combining and restructuring datasets with MATCH FILES, VARSTOCASES, and AGGREGATE, descriptive statistics (FREQUENCIES, DESCRIPTIVES, MEANS, EXAMINE), hypothesis testing (T-TEST, ONEWAY, nonparametric alternatives), regression and modeling (REGRESSION, LOGISTIC REGRESSION), statistical graphics with the declarative GGRAPH/GPL syntax and the legacy GRAPH command, and the macro and scratch-variable facilities that keep a syntax file reusable and reproducible. A one-page syntax appendix closes the book for the fastest possible lookup.

Unlike this series' Python, R, and SQL titles, no SPSS interpreter is available in the environment this book was written in, since IBM SPSS Statistics is commercial, license-locked software with no free interpreter suitable for unattended sandbox execution -- the same situation as this series' SAS and Stata titles. Every numeric result quoted in the book was independently computed in Python or R and cross-checked, and every SPSS command was checked line by line against IBM's official SPSS Statistics Command Syntax Reference for correct syntax. Nothing here was silently fabricated -- where a result rests on cross-verification rather than a live SPSS session, the book says so. If your own SPSS output differs, something in your data or options differs too, and that is worth tracking down before moving on.