To review, 'data view' is used for editing the actual data, whereas 'variable view' is used for editing the attributes of the variables (such as number of decimal places allowed, type of variable, the variable name, variable label, and value label). The screenshot below shows an example SPSS dataset I created for demonstration purposes (as you can see at the bottom of the screenshot, we are seeing the 'variable view', as opposed to 'data view'. For example, 'Gender' may be coded 0 (Males) and 1 (Females). Value Labels: Value labels are labels for coded variables in our dataset. If the variable labels are properly formatted in SPSS, they will show in output tables and graphs, instead of variable names. Variable Labels: Variable labels are composed of a few words that describe what a variable represents. When used in conjunction with the customizable SPSS table 'Looks' function, formatting your variable labels and value labels can make your SPSS results tables nearly ready for publication, immediately after analysis! Fortunately, SPSS syntax offers a fairly straightforward method for assigning proper labels to both your variable labels and value labels.įor those of you unsure about the distinction between the two: Who among us have not been frustrated while wrestling with Microsoft Word?

Unfortunately, that option only leaves additional opportunity for error and confusion, not to mention the inefficiency of editing tables in Microsoft Word. Besides recoding and cleaning variables, a diligent data analyst also must assign variable labels and value labels, unless they choose to wait until after your output is exported to Microsoft Word. Preparing a dataset for analysis is an arduous process.

Spss code sheet