Hi

I'm with others here that students should learn NHST and would just add that 
most statistical procedures have varying shortcomings.  With ESs, for example, 
there is the danger of concluding that a small ES means that the effect is 
trivial ... not true.  And I haven't looked at recent developments in use of 
CI, but wonder how it accommodates things like adjusting for number of 
comparisons in post hoc testing?  Or more complex results (e.g., partitioning 
interaction in mixed factor anova)?

And without following Michael P's wise advice to actually read the article he 
abstracted, I wonder in such studies of unwanted consequences of reporting NHST 
results (i.e., sig vs nonsig) whether they just did the conclusion or reported 
p values, as now recommended by APA (and common sense).  Do people misinterpret 
the difference between an effect with p = .053 versus an effect with p = .048?

Finally, intro stats cannot be the be-all and end-all of statistical learning 
for students going further in psychology (or other fields that use statistics 
... lots on data mining right now in the business world).  We're laying a 
foundation and part of that foundation should be a proper understanding of 
NHST, along with other concepts (e.g., strength of relationships).

Take care
Jim


James M. Clark
Professor of Psychology
204-786-9757
204-774-4134 Fax
[email protected]

>>> Michael Palij <[email protected]> 20-Feb-12 10:13 AM >>>
Okay, I beg your indulgence and participation in an unscientific poll where
you can either post your response to the TiPS list (for discussion) or
email your response directly to me.  I am finishing a book review
on an undergraduate statistics textbook that (a) attempts to eliminate
all null hypothesis signitifcance testing (NHST) in favor of focusing
on effect sizes (ES), confidence intervals (CI), and (old fashioned)
meta-analysis
and (b) encourages research on "statistical cognition" which, according
to the author, shows that teaching NHST causes greater confusion
in students than an ES/CI approach
.
Given that limited description, I'm going to make this into a
2-alternative forced choice question:

Would you use such a textbook as the main textbook in
the first/introductory statistics in psychology course?

[    [  Yes
[    ]  No

Comments?

If you care to, you might comment on whether current intro stat
textbooks do an adequate job of covering issues such as effect
sizes and confidence intervals (these days I use some version
of Gravetter and Wallnau which, in my opinion, do an adequate
job introducing the topics which I assume lay the foundation for
a more advanced undergraduate course in statistical methods).

Thanks in advance for your cooperation.

-Mike Palij
New York University
[email protected] 

P.S. And, no, this not about procrastinating on finishing the book
review. Well, mostly it's not. ;-)

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