Séminaire n°29 + Atelier
Seminar: The New
Statistics: Why, How, and Where Next?
Speaker:
Geoff Cumming, Statistical Cognition Laboratory, School of
Psychological Science, La Trobe University, Melbourne, Australia
Contact :
g.cumming (at) latrobe.edu.au
Date : 11/05/12, 10-12h
Abstract :
Many disciplines rely on null hypothesis significance testing (NHST)
and p values, despite their deep flaws having been known for more than
half a century. I will explain why estimation, based on effect sizes
and confidence intervals, is a much more informative approach. 'The
Dance of the p Values' demonstrates one dramatic shortcoming of p
values: A replication experiment is likely to give a very different
value of p, so p simply cannot be trusted.
I refer to estimation - and its extension, meta-analysis - as The New
Statistics. The techniques themselves are not new, but for most
researchers it would be new, and a highly beneficial change, to switch
from NHST to these techniques. I will describe practical ways to use
the new statistics. I will use ESCI (Exploratory Software for
Confidence Intervals), which runs under Excel, to illustrate concepts
and calculate confidence intervals. ESCI is a free download here.
That website also gives information about my
book:
Cumming, G. (2012). Understanding The New Statistics: Effect Sizes,
Confidence Intervals, and Meta-Analysis. New York: Routledge.
I gave a
short radio talk that summarises the main argument for the new
statistics. The podcast and transcript are available here.
Talk : downloadable here (pps file)
Workshop: The New
Statistics in Practice
Speaker :
Geoff Cumming
Date : 11/05/12, 14-17h
Abstract :
In this workshop I will discuss how to use the new statistics in
practice. Choice of topics will be responsive to the interests of
people attending. I could consider various measures, including
correlations, proportions, and the standardized effect size Cohen’s d.
I could consider a range of simple experimental designs. I will also
discuss meta-analysis. ESCI will serve to illustrate many of the ideas,
and calculate confidence intervals in the different situations. I will
consider statistical power, but will emphasize the advantages of an
alternative approach to planning experiments: Precision for planning.
This approach calculates the N required for our planned experiment to
be likely to give a confidence interval that is not greater than some
specified target length. There will be ample time for discussion, and
for considering data and situations that are of particular interest to
participants.
Talk : downloadable here (pps file)
Entrée libre sur inscription auprès de claudia.fritz (at) upmc.fr