SPSS OMS (Output Management System) converts SPSS output tables into datasets. On some projects, this saves truly vast amounts of time and effort.

Categories that are absent in your data don't show up in your output. However, you may want to include them with zero frequencies. This tutorial demonstrates how to accomplish just that.

SPSS doesn't offer an easy way to set decimal places for output tables. This tutorial proposes a very simple tool for setting decimal places in basic output tables after they've been produced.

There's several ways to open SPSS data files. The right way, however, is by syntax. The way we typically do so in practice may differ somewhat from what you're used to. But give it a shot. It keeps things nicely organized and this eventually saves time and effort.

Before analyzing our data, we check whether they contain any bad cases. If these are present, we need to exclude them from our analyses.

An often requested feature is to export variable and value labels to Excel. This handy tool creates an SPSS Dataset containing these labels. It can either be be saved as an Excel sheet or further edited in SPSS.

"I found a variable "v_4" in an old data file and I can't remember how exactly I created it. The syntax I used got a bit messy, I have different files and they're in different folders. Is there an easy way to find out which syntax files contain the expression "v_4"?"

Setting the decimal places for output is not straightforward. One can exert some control by altering the variable formats. However, for full control, one needs Python Scripting or SaxBasic.

When we start analyzing a data file, we first inspect our data for a number of common problems. For instance, we want to be sure that variables have the right formats, don't contain any weird values and have plausible distributions. This tutorial proposes which steps should be taken and in which order.

This tutorial presents a simple tool for recoding values along with their value labels into different values.