Researcher manipulates drug (placebo vs. real)
Single variable, two level experiment (not enough info to know more)
Dr. Jones manipulated the...
independent variable (stock market?)
Random assignment to a two condition between subject experiment means each person has a BLANK probibility of being in "condition 1" or "condition 2"
50/50 (50%)
All participants do all levels (2x2)
Fully within subjects factorial design
The outcome was the...
dependent variable
The classic example of counterbalancing for order effects is
AB/BA testing
Participants do only one level for each combination of variables (2x2)
Fully between subjects factorial design
Age is a common
Quazi-independent variable
This square can help when counterbalancing for more complicated designs (when more orders are possible)
Latin Square
Age (O/Y) x Drug (Between: low vs. high) x Therapy Intervention (Within: group vs. solo)
2 x 2 x 2 mixed factorial design with age as a Quazi-IV
Researcher collects demographics that are not part of the manipulation. These are BLANK variables
Measured variables
Randomization helps squash pre-experimental differences that could become:
confounds