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Psychology (10,000)

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David Nussbaum (70)

Chapter 7

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PsychologyCourse Code

PSYB01H3Professor

David NussbaumChapter

7This

**preview**shows page 1. to view the full**5 pages of the document.**Chapter 7: True Experiments II

•The emotional salience of the human face reflects an intricate interaction among distinct

features of the face

•Complex experimental designs - which are used when a researcher seeks to manipulate

two or more independent variables at the same time

oAre more realistic

oAre more efficient than experimental analysis limited to a one-at-a-time variable

manipulation

•These complex experimental designs = factorial designs

oA factor is simply another name for an independent variable

•Multifactorial = experiments that vary two or more independent variables

Multifactorial Designs

•All independent variables must have two or more levels

•Single-factor experiments must incorporate one and only on independent variable with

two or more levels

oA researcher can always add a new level to an existing independent variable

•In a multifactorial experiment, an altogether new independent variable is devised and

incorporated into the research design

oEach independent variable can be studied either between subjects or within

subjects

•within subject design = all participants go through all conditions of the

experiment

•Between subject design = participants are separated to each be

exclusively assigned to one of the conditions

•A multifactorial design provides a more realistic model of rich psychological phenomena

oOffers an economical and efficient design to evaluate and to test the separate and

joint influences of one or more independent variables

Notation and Terms

•The simplest multifactorial experiment design contains two independent variables, each

with two levels or values

•Factorial experiments are typically designated or identified by a numbering notation

oExample: 2 x 2

•The number of treatment groups can be calculated by multiplying the

number notations= 4 groups (2 x 2 = 4)

•The number of numbers tells how many factors or independent variables

there are = 2 independent variables (2 terms, 2 & 2)

•Number of values tells how many levels of the independent variable there

are = each IV has 2 levels (each term's numerical value = 2)

oAllows us to examine all these conditions

Theory and Experimentation

•Theory provides us with the conceptual framework for how particular psychological

phenomena might work in real life

oExample: theory of embodied cognition = conceptual model for us to understand

how we experience, perceive, and communicate emotional information

•We perceive and think about emotion, we re-enact or re-experience its

perceptual, somatovisceral, and motoric features

•Theory and experimentation are closed intertwined

•Theory guides how an experiment is designed, how independent variables are measured,

and what specific hypotheses are tested

A Complex Within-Subjects Experiment

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•Approach-avoidance motivation - eye gaze direction and facial expressions can both

share informational values as signals of approach, propelling behaviour forward, setting the

stage for direct expression, confrontation or flight, conversely, they may fuel avoidance,

triggering inhibition, culminating in flight from negative stimuli, of potential danger and

threat

•Social signaling system - proposal that facial expression of emotions and gaze

direction operate and governs our basic evolved behavioural tendencies for approach or

avoidance

Decoding Facial Expressions of Emotion

•Experimentation often deconstructs complex phenomena

•In a within-subject design, each participant serves as his or her own control, these

individual differences are effectively held constant

oMore economical than between subject designs

•Fewer participants are needed to perform the experimental task

oFewer participants require that you collect more observations per participant

•Reliability of a test can often be increased by simply adding more items

•Same principle is good to keep in mind in light of the reduced number of participants that

is commonly used in within-subjects designs

Main Effects

•In a factorial experiment, the effects of each independent variable on a dependent

variable are referred to as the main effect of that independent variable

oA main effect can be calculated for each independent variable

Interactions

•A statistical interaction occurs when the effects of one level of the independent variable

depend on the particular level of the other independent variable

Interpreting Results of Multifactorial Designs

•Factorial designs provide two distinct sources of information:

1. Main effect of each independent variable by itself and

2. Any interaction effect of the independent variables

•Main effects are statistically independent of interaction effects but still have significant

interactions effects or vice versa

•To interpret results generated from a multifactorial 2 x 2 experiments - look to see if

there is an interaction between the independent variables, and if so, we interpret the

interaction first, before the main effects

•An interaction indicates any interpretation of a main effect of an independent variable by

itself will be misleading

oThe interaction tells us that the effects of the independent variable depend upon

the particular level of the independent variable

oTherefore cannot interpret a main effect of an independent variable without first

taking into consideration whether that effect interacts with another independent

variable

•We often graph main effects and interactions as a way to help us to understand and

interpret our data

•A simple main effect compares the influences of one level of an independent variable at a

given level of another independent variable

2 x 2 Logic

•Simplest of the complex designs, yet not that simple

•Proves a direct test of the main effect of each of the two independent variables as well a

direct test of the interaction effect between them

•Either of the two independent variables may or may not affect the dependent variable

and an interaction between the two independent variables may or may not be present

•Additivity and no interaction = synonymous

oIf you have two main effects but no interaction, we can say the values of one

independent variable exert a similar, additive effect on the values of the independent

variable

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