Hi, all --
Next year I've planned on developing a stats/methods integrated text (I have
some sabbatical time). More and more, though, lately I've been reading that
"we're doing stats wrong" and need to start moving to Bayesian stats. I
understand and appreciate the arguments. I think they're right. The recent
Psych Science has a bevy of articles about it, exacerbated, I'm sure, by Bem's
JPSP article.
Our program is essentially a grad-school-prep program, and the text will be for
these students: all grad-school-bound, and smart. But most are going into the
helping, rather than research-side of psych. But they'll get PhDs.
Can I get a show of hands to help me decide whether or not I should a) include
only Bayesian hypothesis testing, 2) both trad and Bayesian hypoth tests, or
iii) just the trad stuff.
It's a year-long course with a lab (I get them 6 hours a week for a year), and
right now they come out knowing things all the way through mixed-model
factorial ANOVA.
Should I back off the hard-core experimental design (ANOVA) and move toward
this recent (sorta) issue about how we have been doing hypothesis tests?
What thinkest thous?
m
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Do not judge me before going to www.damnyouautocorrect.com.
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