Psychology 7

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Psychology 7 Experimental Psychology
Complex Designs
Professor Gallagher and his controversial
technique of simultaneously confronting the fear
of heights, snakes, and the dark.
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Mean 78
Approx. Curve 88-100 A 79-87 B 64-78 C 50-63 D 50 F
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Important Note

• Lecture is canceled for 11/20 (next Tuesday)
• Office Hours will be held instead from 10 AM 12
  PM in Psych East 2829 if you wish to see your
  exams and go over the questions that you missed.

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Factors and Levels

• Factor is another term for independent variable
• Experiment Randomly assign subjects to drink
  coffee or drink de-caf
• One factor whether or not drink coffee
• Levels refer to the different conditions within a
  factor
• 2 levels in the coffee example regular coffee
  vs. de-caf
• Experiment with a 3rd group drink caffeinated
  soda would have 3 levels but still one factor

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One Factor Designs with 2 Levels

• 2 basic reasons for having 2 levels
• Need more than 2 to detect curvilinear or complex
  relationships between variables
• May want multiple control groups/be interested in
  multiple conditions

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Yerkes-Dodson Law
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Bandura Study of Imitative Aggression

• Children (3-5 yrs) assigned to 1 of 3 conditions
  
• Observe aggressive adult beat up Bobo doll
• Observe nonaggressive adult not beat up Bobo doll
• No exposure to any adult model
• Matched Pairs Design Children were enrolled in
  Stanford Universitys Nursery School
• Rated by teachers for degree of aggressiveness
• Matched for aggressiveness before being randomly
  assigned to conditions
• Hypotheses (1) Kids exposed to aggressive
  models would perform more aggression than those
  in other 2 groups, (2) Exposure to nonaggressive
  model would inhibit aggression (prediction no
  exposure kids aggression than nonaggressive
  condition)

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• Dependent variable measured in a different room
  in the absence of the adult models
• Prior to the test for imitation, however, all
  subjects were subjected to mild aggression
  arousal to insure that they were under some
  degree of instigation to aggression.
• Experimenter brought kids into room with
  attractive toys and after letting them get
  engaged with them ( 2 min.), remarked that
  these were her very best toys, that she did not
  let just anyone play with them, and that she had
  decided to reserve these toys for the other
  children.
• Modeling apparently doesnt work without this
  added instigation
• Observers counted of aggressive acts in
  specific categories behind one-way mirror over 20
  minute interval

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Results
Bandura, Ross, Ross (1961)
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Factorial Designs
Factorial designs involve 1 independent
variable or factor All levels of each
independent variable are combined with all levels
of the other independent variables
Example Balanced Placebo Design Study
Factor 1 Level 1 Level 2 Factor 2 Level
1 Level 2

• Alcohol expectations
• Expect vodka
• Expect tonic
• Alcohol intake
• Drank vodka
• Drank tonic

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Alcohol Study
Expectations
Alcohol
No alcohol
Tonic
Intake
Vodka
...a 2(rows) x 2 (columns) design
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Multiplicative Notation
A 3 x 4 factorial design
2 Factors with 3 and 4 levels
12 cells total (3 x 4)
A 2 x 2 x 2 factorial design How many
factors? How many cells?
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Alcohol Example
Expectations
Alcohol
No alcohol
Group 1 average
Group 3 average
Tonic
Group 2 average
Group 4 average
Intake
Vodka
Usually, averages are in the cells
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Main Effects

• Main effects are the effects of each independent
  variable considered separately
• E.g., does actually drinking vodka produce higher
  levels of shock delivered to a learner than
  drinking tonic? (main effect of alcohol intake)
• Main effects compare the effects of levels within
  a factor averaged across all levels of the other
  factors
• The number of possible main effects is equal to
  the number of factors

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Main Effects in Baseball

• Right-handed (RH) vs. Left-handed (LH) batters
  face either a Right-handed (RH) or Left-Handed
  pitcher

A main effect looks at the effect of 1 factor
while ignoring the others
Pitcher
RH
LH
Main Effect of Handedness LH RH
RH
Batter
LH
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Interaction Effects

• When the effect of one independent variable
  depends on the level of another independent
  variable
• Cannot fully understand the influence of one
  independent variable without reference to another
  independent variable

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Interaction Effects in Baseball

• External Validity Extent to which results of a
  study would be found with different participants
  or in a different setting/situation
• Interactions related to external validity Does
  an independent variable have the same effect in a
  different situation or with different
  participants? (with the different situation
  represented by another factor).

Study 1
Study 2
RH
RH
Batter
Batter
LH
LH
Right-handed Pitcher
Left-handed Pitcher
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Main Effects in American Idol
Yeah!! Go Corey!
Type of Song
Overall Avg.
Love Song
Rock Song
150
Main Effect of Sex F M
Male
Sex of Singer
Female
250
DV of votes (in thousands)
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Graphing Results of Factorial Designs
For Main Effects Compute the averages for each
condition and plot as bar graphs Which is larger?
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Graphing Results of Factorial Designs
For Interaction Effects Plot all of the data as
line graphs. Nonparallel lines indicate an
interaction.
Pitcher
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Alcohol Study in Factorial Notation
Expectation
Alcohol
No Alcohol
Alcohol
4.3
Actually Get
4.2
No Alcohol
5.05
3.45
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Main Effects in Alcohol Study
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Simple Main Effects

• Simple main effects examine the effects of one
  factor at one level of another factor
• E.g., do right-handed batters have higher batting
  averages than left-handed batters against
  left-handed pitchers?
• Question is isolated to left-handed pitchers (one
  level of the pitcher handedness factor)

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Simple Main Effects
Simple Main Effects of Batter Handedness at 2
levels of pitcher handedness
Pitcher Factor Level1
Pitcher Factor Level 2
RH
RH
Batter
Batter
LH
LH
Right-handed Pitcher
Left-handed Pitcher
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Simple Main Effects in American Idol
Yeah!! Go Corey!
Type of Song
Overall Avg.
Love Song
Rock Song
150
Main Effect of Sex F M
Male
Sex of Singer
Female
250
DV of votes (in thousands)
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Graphing Results of Factorial Designs
For Interaction Effects Plot all of the data as
line graphs. Nonparallel lines indicate an
interaction.