Research wor
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WORKSHOPS ON FORMAL EVIDENCE FOR ALTERNATIVE
HYPOTHESES
Research workers in many fields are realizing the
substantial limitations of statistical tests, test statistics, arbitrary
α-levels, P-values, and dichotomous rulings concerning “statistical
significance.” These traditional
approaches were developed at the beginning of the last century and are being
replaced by modern methods that are much more useful. These methods rely on the concept of
information loss and formal evidence. They provide easy-to-compute quantities such at the probability of each
hypothesis/model and evidence ratios. Furthermore, simple methods allow formal inference (e.g.
prediction/forecasting) from all the models in an a priori set (“multimodel inference”).
I am planning to offer several 2-day courses on the
Information-Theoretic approaches to statistical inference during January,
March, and April, 2012. These courses
focus on the practical application of these new methods and are based on
Kullback-Leibler information and Akaike’s information criterion (AIC). The material follows the recent textbook,
Anderson,
D. R. 2008. Model based inference in the
life sciences: a primer
on evidence.Springer, New York, NY. 184pp.
A copy of this book, a reference sheet, and several
handouts are included in the registration fee. These courses stress science and science philosophy as much as
statistical methods. The focus is on
quantification and qualification of formal evidence concerning alternative
science hypotheses.
These courses can be hosted, organized, and
delivered at your university, agency, institute, or training center. I have given 55-660 of these courses and they
have been well received. The courses are
informal and discussion and debate are encouraged. Further insights can be found at
http://aicanderson2.home.comcast.net
Details on hosting such a course are given at
http://aicandersion1.home.comcast.net -- then click on “Hosting a Short Course” on the left.
If you are interested in hosting a course at your
location, please contact me. Thank you.
David R. Anderson
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