Chapter 4 Studying Behavior

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Chapter 4Studying Behavior

• Variables
• Can have levels
• Types
• 1. Situational
• Characteristic of the environment
• 2. Response
• Reaction time, performance on a task
• 3. Participant or subject
• Gender, personality trait
• 4. Mediating
• Personal responsibility

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Operational definition

• A definition of the variable in terms of the
  operations used to measure it the variable
• Defines a construct by specifying how it the
  construct is measured or manipulated
• Converts an abstract concept into concrete,
  situation specific terms
• For example
• In animal research ? Hunger deprivation for at
  least 12 hours
• In human research ?
• How hungry are you at this moment?
• Not at all
• Slightly
• Moderately
• very

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Operational definition

• Necessary for empirical study
• Can be easily assigned or abstract
• Helps to communicate ideas in the scientific
  community
• However, researchers from different labs can
  define similar things differently

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Variables

• Usually thought to have a cause and effect
  connection
• Independent variable
• The cause
• Manipulated in an experiment
• Must have 2 or more levels
• Can be quantitative (i.e. different doses of a
  drug) or qualitative (i.e. changing the sequence
  of words in a memory test).
• It is usually on the horizontal axis (x axis) on
  a graph
• Dependent variable
• The effect
• Measured in an experiment
• Can have one or more levels
• It is usually on the vertical axis (y axis) on a
  graph

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• For example
• Homer notices that his shower is covered in a
  strange green slime. His friend Barney tells him
  that coconut juice will get rid of the green
  slime. Homer decides to check this this out by
  spraying half of the shower with coconut juice.
  He sprays the other half of the shower with
  water. After 3 days of "treatment" there is no
  change in the appearance of the green slime on
  either side of the shower.
• What was the initial observation?
• Identify the
• Control Group
• Independent Variable
• Dependent Variable
• What should Homer's conclusion be?

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Relationships b/w variables

• Comparing values along a numeric scale
• Positive linear relationship
• Increases in one variable (on x axis) are
  accompanied by increases in another variable (y
  axis)
• For example
• Are fast talkers more persuasive?
• Plot words spoken per minute (x axis) against
  attitude change (y axis)
• Negative linear relationship
• Increases in one variable are accompanied by
  decreases in the other variable
• For example
• Does the number of people in a group predict how
  efficient the group will be?
• One study found that as the size of the group
  increased, the amount of noise decreased.

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Relationships b/w variables

• Curvilinear relationship
• Increases in one variable are accompanied by
  decreases and increases in the other variable
• Referred to as U shaped curves or inverted U
  shaped curves
• For example
• In dose response studies, in the case of a U
  shaped curve,
• low doses can cause high responses
• Intermediate doses can have low effectiveness
• High doses can cause high responses
• No relationship
• For example
• Does the length of the tail of a bird predict how
  many matings it will engage in?

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Nonexperimental vs. experimental methods

• Nonexperimental
• Making observations of the variables of interest
• Asking others to describe their behavior
• Examining public records
• Allows for observation of covariation between
  variables
• Correlational method

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Nonexperimental vs. experimental methods

• Problems with correlational method
• Direction of cause and effect
• The 3rd variable problem

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Nonexperimental vs. experimental methods

• Experimental
• Involves direct manipulation and control of
  variables
• The researcher manipulates the 1st variable and
  observes the response
• Reduces ambiguity in the interpretation of
  results
• The direction of cause and effect is clear
• Attempts to eliminate the influence of all
  potential confounding variables
• Control of extraneous variables

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Nonexperimental vs. experimental methods

• Experimental control
• Control of extraneous variables
• Variables held constant cannot be a confounding
  variable
• Accomplished by treating participants/subjects in
  all groups in the experiment identically
• Randomization
• Ensures that the extraneous variable is equally
  likely to affect all participants/subjects
• Eliminates influences of individual
  characteristics
• Ensures that the composition of
  participants/subjects in each group is identical

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Causality

• Inferences about causality require 3 elements
• -
• -
• -
• Is the cause necessary and sufficient for the
  effect to occur?

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Choosing methods

• Field experiment
• Done in the field, not the laboratory
• The independent variable (i.v.) is manipulated in
  a natural setting
• Advantage
• -
• Disadvantages
• -
• -
• -

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Evaluating Research

• Validity
• The accurate representation of information
• Different types (each gives a different
  perspective on a research investigation)
• Construct validity
• The adequacy of the operational definition of
  variables
• The measure has construct validity if it measures
  what it is supposed to
• Face validity
• Criterion oriented validity
• Internal
• The ability to draw conclusions about causal
  relationships from the data
• Easier to prove when using the experimental method

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Evaluating Research

• Internal
• Threats
• Biased assignment of subjects
• Experimental confounds (i.e. performing
  systematic differences)
• Differential attrition
• Pretest sensitization
• External
• The extent to which the results can be
  generalized to other populations and settings
• Can these results be replicated? With different
  participants?
• No method is superior to another