Data preparation in SPSS
The unglamorous work that eats more of your time than the analysis itself.
8 modules from the SPSS & Research Methods curriculum. Covers everything from opening SPSS for the first time to writing your own syntax.
What you'll learn
By the end of this course
- Navigate the SPSS workspace confidently
- Build a codebook and enter data correctly the first time
- Import data cleanly from Excel, online forms, Kobo, and REDCap
- Clean data you didn't collect yourself before it wrecks your analysis
- Handle missing data without quietly biasing your results
- Recode, compute, and score variables correctly
- Restructure a dataset — select, split, merge, go long or wide — when the analysis demands it
- Write and reuse syntax instead of clicking through the same steps twice
Curriculum
8 sections · 8 lessons
Section 1
8 modules
Section 1
- The SPSS workspaceSPSS looks like one program. It is really four windows that pass work to each other, and each one saves a different kind of file.~25 min
- Codebook and data entryThe order is the content of this module. Every step is cheap while the ones after it have not happened yet, and expensive once they have.~30 min
- Getting data in: Excel, Forms, Kobo, REDCapEvery import produces a working file, not a finished one. Keeping them separate is what lets you answer “where did this number come from?” a year later.~25 min
- Cleaning data you did not collectDuplicates come first because a duplicated case multiplies every other problem it carries. Outliers come last because you cannot judge an extreme value until the impossible ones are gone.~35 min
- Missing dataYou cannot choose a method before you have a view about the mechanism. Almost every bad decision about missing data is question 3 answered without question 2.~30 min
- Transform: recode, compute, scoreEvery transformation in SPSS is one of these four, and every one of them writes to a new variable and leaves the original alone.~35 min
- Restructure: select, split, merge, long/wideEvery operation in this module answers one of those two questions. The first three are reversible and persistent; the last three change the file itself.~30 min
- Syntax, and why you should never click twiceThis is the whole of Track B, in the order the modules taught it, as five sections of one text file you can re-run from nothing.~30 min
About this course
Data preparation in SPSS is where most researchers actually lose their weeks — it's under-taught everywhere, which is exactly why it matters. This track covers the ground between "I have a dataset" and "I can trust this dataset," from first opening the software to writing syntax you can reuse.
Eight modules, about 4 hours total. The SPSS workspace opens things up, feeding both the codebook and data-entry module and the module on getting data in from Excel, forms, Kobo, and REDCap. From there, cleaning data becomes the hub — missing data and variable transformation both build on it, and transformation itself branches into restructuring datasets and writing syntax.
This track assumes you already know how to classify variables by type and level of measurement, since the codebook module builds directly on that.
Who it's for
- Anyone about to work with someone else's messy dataset for the first time
- Researchers who've learned the statistics but never learned the workspace
- People tired of redoing the same manual steps by hand every time
What you'll need
- Variables and levels of measurement (from Track A) covered first, since the codebook module depends on it
- Access to SPSS — this track works directly in the software, not just theory
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