We also took a range of 'subjective' measurements about how the person felt - about pain, about swelling, about confidence, about wellbeing. This is still quantitative data because it asks them to score the feeling from 0 to 6, so we have a range of numbers, taken before and after the study ( so 7 weeks apart). Then we have the qualitative data. This kind of data is generally words, and involved interviews taken after the end of the study, just chatting to the participants and asking them about their experiences, before, during and after the project. As you can imagine, that's a lot of words, but even this data has to be analysed.
As for the numbers, we want to know whether those swollen arms were smaller after than they were before yes? Of course we do, but its not as simple as measuring the difference, we have to measure them before treatments began ( for 3 weeks) just to see how their size fluctuates normally.
Then we need to compare them with eachother ( good arm v bad arm) before and after every session. Then we compare all the befores, then we compare all the afters, then we compare every weeks' data, for every person. Then we look at percentages, then we look at the possibilty of coincidence or chance, and run statistical tests on this.
As for the arm measurements. the biggest part of the objective, quantitiative data is just about done.
i'm just about to start on the subjective quantitative data ( scores of feelings) and run some tests on those. Then it will be the turn of the interview data, which has to be analysed is a specific way. That's few weeks away yet.
The data is still looking great, whichever way you look at it, upside down or sideways, it is very difficult to pick holes in it - and that's what we're doing really. Trying to understand what's going on, and asking - could this be a fluke?