Re: [Gretl-users] May I be bold? Meta-suggestions

If it is not undue intervention as an humble student of Econometrics ( I am 70 years old ) I feel The various assumptions about Normal Distribution are hardly met in real life data. If one has sound theory yest there is no co integration of data or unit root is present then there are two golden ways. A. Increase the sample size B. Reexamine the theory Incidentally I may comment that the concept of spurious regression has been oversold On Fri, May 2, 2014 at 8:54 AM, Tim Nall <tnall.ling(a)gmail.com&gt; wrote: > > All, > > Again please refer to previous disclaimers about the fact that I > certainly and truly have no idea what I am talking about w. respect to > statistics, and perhaps with respect to other issues as well. > > In an earlier post, someone or other expressed a concern that gretl > might be perceived as a toy program that is purely for educational > purposes, and not for serious research. I have no idea whether or not > that's the case, but I would suggest that focusing on pushing gretl as > a serious tool is not the only path toward your ultimate goal. Me > personally, I would recast a perceived shortcoming as a serious > strength: push it as an educational tool. The way to do so, as I > mentioned earlier, is by writing a book. The book should be > data-centric and outcome-centric. That is, the traditional teaching > approach would be to think, "I have x number of statistical topics to > cover, and they can be ranked in terms of difficulty and inheritance > of concepts from one another, so I will present them according to that > rank. I will discuss the math and theory first, and perhaps (or > perhaps not) tack on a skimpy example in the end." This is a > forest-for-the-trees approach IMHO. Me personally, i would approach > the book as "You have (this) type of data, and you want (this) type of > outcome, so you should use (this) type of model, unless your data has > (these) conditions, and the way to deal with (these) conditions is > (chapter)." > > I can truly embarrass myself here by offering my own recent exp. as an > example: in my very modest research, a set of 10 OLS regressions (on > time series data) that were truly beautiful and perfect in every way > (they conformed very, very precisely to my initial set of hypotheses) > sat on the pages of my document for months before I realized that the > results were spurious due to non-stationary data. [Econometricians and > statisticians can politely refrain from giggling.] So ch. 1 of your > book, rather than immediately presenting the nuts and bolts of OLS, > could first present the same sort of case (very quickly). And so on. > Make top-level ideas (such as which problems to check for before > considering any given approach) *very* easy to find at a glance. Got > math? It goes in appendices. > > And here's the point: you would want your book to help gretl catch on > as an educational tool, but sprinkled throughout the book you could > also mention (w. brief details) its ability to do serious research. No > harm done. Then if it catches on in the former context, eventually > (lag a couple years) people will pick up on the latter idea -- also > realizing, hey, you know, it's free. > > So that's all I have to say. Thank you for your patience. TMN > _______________________________________________ > Gretl-users mailing list > Gretl-users(a)lists.wfu.edu > http://lists.wfu.edu/mailman/listinfo/gretl-users _______________________________________________ Gretl-users mailing list Gretl-users(a)lists.wfu.edu http://lists.wfu.edu/mailman/listinfo/gretl-users