Although this is really a religious rather than scientific debate which is unlikely to lead to any concensus, I want to respond to some of Jim Roper's comments.
The fact that you can learn a lot by looking at plots does not mean the that "results are so glaringly obvious". Humans are very good at pattern recognition and often can see what is present in a plot better than they can analyse numerical data. Also, plots often show unexpected features which lead to new knowledge - they are not just for hypothesis testing. On several occasions I have been consulted by people who are quite expert at statistics who cannot interpret their data, and who were surprised that by plotting the results in the right way a clear answer leaped out at them. Of course they then had to confirm the results with statistics, but that is mainly to get the paper past referees. Jim ends with the usual comment that if the statistics are carried out by someone who is really good at stats, the results will be good. That may be true, but good statisticians are pretty rare beasts, and in the average lab the plotting method is just as reliable as textbook stats. Some of you may recall a post of mine a couple of years ago where I surveyed a lot of statistically sophisticated fisheries scientists to see if they could add two numbers (what is 100+-3 + 100 +-4?) and only one person came up with the answer - but he was very unsure of himself, and couldn't figure out how to multiply the numbers. Just a glance through any journal will quickly show that most biologists have little idea of significance and represent their results with exaggerated precision. In a perfect world maybe we could trust all statistical analyses, but we ain't there yet. Bill Silvert ----- Original Message ----- From: "James J. Roper" <[EMAIL PROTECTED]> To: <[email protected]> Sent: Wednesday, July 18, 2007 3:43 PM Subject: Re: ECOLOGY Mathematics and the metamathematics of evasive ecology? Re: Request: Data sets for biocalculus project > Mattheus, > > You are showing some misunderstanding of the use of statistics. A few > observations. > > 1. If your results are so glaringly obvious, then the question was > probably not very interesting, or a logical consequence of the methods. > > 2. Questions that are not so simple need statistics to discover the > probability of something happening when it is not obligatory that it > happen. > >> statistical tests when you can simply draw a plot and >> your conclusion comes? > 3. A plot can mislead. >> I need to learn that populations must >> be normal, they must be homoscedastic, there are at >> least 3 models for ANOVA, there is something out there >> with the name of ANCOVA, and I have no single idea if >> this is useful for me or not...
