Name that tune.
Song title? Performer(s)?
R.G. Bias | rbias@ischool.utexas.edu |
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Scientific Method (continued)
“Finding New Information”
3/28/2010
R.G. Bias | rbias@ischool.utexas.edu |
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Objectives
 I want to arm you with a scientist’s skepticism, and a
scientist’s tools to conduct research and evaluate others’
research.
 Swoopin’ out of “scientific method” and “experimental
design” and into “statistics.”
-
Randolph – remember to take roll.
R.G. Bias | rbias@ischool.utexas.edu |
SIQR
 The Measure of Spread used along when
you use median as your Measure of
Central Tendency.
 SIQR = (Q3 – Q1)/2
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Independent Groups Design
 Each group represents a different
condition as defined by the independent
variable.
 E.g., two 2nd-grade classes (matched for
teacher, perhaps other variables) receiving
two different reading-instruction courses.
 E.g., two different groups each getting a
different dosage of some drug.
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R.G. Bias | rbias@ischool.utexas.edu |
Let’s step back a minute
 An experiment is “personkind’s way of asking
nature a question.”
 I want to know if one variable (factor, event,
thing) has an effect on another variable – does
the IV systematically influence the DV?
 I manipulate some variables (IVs), control other
variables, and count on random assignment to
wash out the effects of all the rest of the
variables.
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R.G. Bias | rbias@ischool.utexas.edu |
Challenges to Internal Validity
 Testing intact groups. (Why is the group a group? Might
be some systematic differences.)
 Extraneous variables. (Balance ‘em.) (E.g.,
experimenter).
 Subject loss
– Mechanical loss, OK.
– Select loss, not OK.
 Demand characteristics (cues and other info participants
pick up on) – use a placebo, and double-blind procedure
 Experimenter effects – use double-blind procedure
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R.G. Bias | rbias@ischool.utexas.edu |
Another design (like “Independent Groups
Design”
 Natural Groups design
– Based on subject (or individual differences)
variables.
– Selected, not manipulated.
– Remember: This will give us description, and
prediction, but not understanding (cause and
effect).
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R.G. Bias | rbias@ischool.utexas.edu |
We’ve been talking about . . .
 Making two groups comparable, so that
the ONLY systematic difference is the IV.
– CONTROL some variables.
– Match on some.
– Use random selection to wash out the effects
of the others.
– What would be the best possible match for
one subject, or one group of subjects?
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Themselves!
 When each test subject is his/her own
control, then that’s called a
– Repeated measures design, or a
– Within-subjects design.
(And the independent groups design is called
a “between subjects” design.)
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Repeated Measures
 If each subject serves as his/her own
control, then we don’t have to worry about
individual differences, across experimental
and control conditions.
 EXCEPT for newly introduced sources of
variance – order effects:
– Practice effects
– Fatigue effects
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Counterbalancing
 ABBA
 Used to overcome order effects.
 Assumes practice/fatigue effects are
linear.
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Which method when?
 Some questions DO lend themselves to
repeated measures (within-subjects) design
– Can people read faster in condition A or condition B?
– Is memorability improved if words are grouped in this
way or that?
 Some questions do NOT lend themselves to
repeated measures design
– Do these instructions help people solve a particular
puzzle?
– Does this drug reduce cholesterol?
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R.G. Bias | rbias@ischool.utexas.edu |
Remember . . .
 We are running an experiment to try to see
if two (or more) levels of an IV differentially
influence a DV.
 We hope to find a difference.
 Finding NO can mean one of two things:
– Truly there’s no difference.
– Our test – our experiment – just wasn’t good
enough, or sensitive enough, to detect the
difference.
R.G. Bias | rbias@ischool.utexas.edu | 14
References
 Hinton, P. R. Statistics explained.
 Shaughnessy, Zechmeister, and
Zechmeister. Experimental methods in
psychology.
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