*Overall it was about half the time in Journals, but in the Nature/ Science Journals it was wrong in about 95% of cases. So they are setting the bad example *

*After we called them on thi*s, t*hey introduced reporting standards. Did they and their referees learn about the statistics?*

So recently we got this figure in a **Nature Journal** and the work was splashed across the media..........The great new hope.

*So we looked as the data*
**Figure legend. **Clinical scores of two independent EAE experiments at d23 post disease induction. Individual scores as well as the mean score of two independent experiments are shown. Control: n=10, vehicle: n=13, xxxxx-345: n=11. Control versus vehicle: P=0.620, control versus xxxxx-345: P=0.017, vehicle versus xxxxx-345 P=0.029. * indicate P values <0.05 and ** indicate P values <0.005 based on a non-paired Studentâ€™s t test. Error bars are s.e.m.

There is a thought in clinical trial studies that you should supply *the primary data so it can be re-analysed. Many companies now willingly do this. This probably will occur or science papers too.*

*So in the figure above they provide primary data. In the drug-treated animals the scores appear to be: 0, 0 ,0, 0.5, 0.5, 2, 2.5, 3, 3.5, 3.5, 3.5 n=11 in vehicle scores appear to be: 0.5, 2.5, 2.5, 2.5, 2,75, 2.75, 3, 3.5, 3.5, 3.5, 3.5, 3.5, 3.5 n=13. *

*Do a t test drug verses vehicle and you get p=0.029 (as in the legend to the figure above) so all is fine and drug is great. The media go mad.....an its the next best thing since sliced bread:-) *

*However, you should not do a t test on this type of data. The assumptions of a t test as that the data is (a) normally distributed. You test this and it passes the test p=0.152,*

*However, it also assumes that (b) data groups have equal variances (the square of standard deviation). Test for that and it fails P<0.05. So it is not valid to do a t test on this data but importantly it is not valid to do a t test on this data, because the data is not parametric, it is non-parametric.*

So do a non-parametric test on the data like the Mann Whitney U test . This has less power to detect differences than a t test.

Do this on the data above and P=0.082.........Ooooops.
*So now do drug verses untreated as well and this also fails P=0.121, so not even a trend:-)*

*There is no statistically significant effect. The drug has not worked! **So you accept this or do more studies to show if this so called trend is real or not, harder to do in humans, much easier to do in animal studies.*

*Simple school-boy stuff. All the reviewers need to do is read:*