Every module we teach, and exactly what is in it
Research statistics taught the way they are actually used — the assumption that chooses the test, the SPSS path in full, and the sentence that reports it.
44
modules planned
25
available now
23h 20m
of learning time
6 modules · Clear filters
B · Data preparation in SPSS
Cleaning data you did not collect
Duplicates 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.
Missing data
You 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.
Transform: recode, compute, score
Every transformation in SPSS is one of these four, and every one of them writes to a new variable and leaves the original alone.
Restructure: select, split, merge, long/wide
Every operation in this module answers one of those two questions. The first three are reversible and persistent; the last three change the file itself.
C · Describing data
Normality and distribution checks
What "assumes normality" actually refers to, and the fact that it is usually the residuals and not the raw variable.
H · Reporting and defence
Defending your analysis
## Suggested bundles
How it is sold
Take one module, a track, or the whole thing
Every module can be bought on its own if you only need one test. Most people take a programme — a named bundle that covers a whole job of work — and the modules you have already finished carry across if you upgrade later.
See the programmes