In some disciplines (psych, ed, nursing, etc), Research Methods is taught as another course. However, both courses should identify the relation between course contents.
G Robin Edwards wrote: > In article <uon58.2302$[EMAIL PROTECTED]>, > Donald Macnaughton <[EMAIL PROTECTED]> wrote: > > At great length, and with many quotes, on a very interesting topic. I > fear I may have missed the original postings on this thread, though. > > There is however one area that seems not to have been addressed. This is > the field of statistical design of experiments. The word "design" > appears just once in the article, in connections with the t test. > > I am really disappointed that there was not some emphasis on the value of > correctly designed experiments at all levels in the sciences, both "hard" > and "soft". > > As a non-statistician, non-mathematician and non-academic (merely a > practical chemist who spent his entire working life in industry) I > introduced myself to statistics via the experiment design route using > Brownlee's "Industrial Experimentation" in 1956. > > The elegance of simple ANOVA became apparent even to me, but the > introduction to the ideas of "design" were even more exciting. Many > practical scientists at "bench" level can I feel readily appreciate many > of the concepts of "design" and thus the notion of constructing a model > which their experimental work will address and hence "prove" or "fail to > support" the underlying hypotheses. > > This I feel is the way to get otherwise sceptical scientists and > engineers into the way of considering their practical real-life problems > as ones that require an "holistic" approach. Few industrial > investigations are single variable problems. > > My belief and experience is that too much emphasis on the formal > mathematical exposition of statistical ideas - however relevant they are > to statistics majors - serve only to distance the experimental scientist > from the huge advantages to be gained from making use of designed > experiments in a complex world. > > Quite simple examples can serve to generate acceptance and even > enthusiasm for what we might regard as a rational approach but which > might otherwise be discouraging for the newcomer to statistical design of > experiments. I've proved this to myself time and again in an industrial > context. > > -- > Robin Edwards ZFC Ta Serious Statistical Software > REAL Statistics with Graphics for RISC OS machines > Please email [EMAIL PROTECTED] for details of our loan software. ================================================================= Instructions for joining and leaving this list, remarks about the problem of INAPPROPRIATE MESSAGES, and archives are available at http://jse.stat.ncsu.edu/ =================================================================
