Personality, 9e Jerry M. Burger © 2016 Cengage Learning. All Rights Reserved.
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Transcript Personality, 9e Jerry M. Burger © 2016 Cengage Learning. All Rights Reserved.
Personality, 9e
Jerry M. Burger
© 2016 Cengage Learning. All Rights Reserved. May not be copied, scanned, or duplicated, in whole or in part, except for use as permitted in a license distributed with a certain product or service or otherwise on a password-protected website for classroom use.
Personality Research
Methods
Chapter 2
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Chapter Outlines
Hypothesis-testing approach
Case study method
Statistical analysis of data
Personality assessment
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Hypothesis-Testing Approach
Theory: General statement about the
relationship between constructs or events
Differ in the range of events or phenomena they
explain
Characteristics of a good theory
Parsimonious - Explains the phenomenon in
simple terms
Useful - Generates testable hypothesis
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Hypothesis-Testing Approach
Hypothesis: Formal prediction about the
relationship between two or more variables
that is logically derived from the theory
A theory is unaccepted if empirical
investigations consistently fail to confirm
predictions
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Figure 2.1 - Example of the
Hypothesis-Testing Approach
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Types of Experimental
Variables
Independent: Determines how the
groups in the experiment are divided
Is manipulated by the experimenter
Known as treatment variable
Dependent: Measured by the investigator
and used to compare the experimental
groups
Known as outcome variable
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Interaction of Experimental
Variables
How one independent variable affects the
dependent variable depends on the other
independent variable
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Manipulated Versus Nonmanipulated
Independent Variables
Manipulated independent
variable
Begins with a large number of
participants
Randomly assigns participants
to experimental groups
Researchers assume that all the
differences will be evened out
Nonmanipulated independent
variable
Exists without the researcher’s
intervention
Investigator does not randomly
assign participants to a condition
Researcher cannot assume the
people in the two groups are
identical
Difficult to find cause-and-effect
relationships
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Prediction Versus Hindsight
Accurate predictions can be made if a
scientist has a legitimate theory
Purpose of research is to provide support
for a hypothesis
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Prediction Versus Hindsight
Researchers:
Generate a theory
Make a hypothesis
Collect data that supports or opposes
hypothesis
Unpredicted findings by the researchers are
the basis for future hypotheses and research
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Replication
Examines participant populations different
from those used in the original research
Helps to determine whether the effect
applies to larger number of people or is
limited to the kind of individuals used in the
original sample
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Replication
Determining the strength of an effect by
how often it is replicated is difficult
File Drawer problem
Investigators publish and report research only
when they find significant effects
Failed attempt at replication makes researcher
to decide something has gone wrong
Leads research being stored in a file drawer and
never reported
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Case Study Method
In-depth evaluation of individuals
Participant is a psychotherapy client
suffering from a problem that interests the
investigator
Researcher records in detail:
Person’s history
Current behavior
Changes in behavior
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Case Study
Data are usually descriptive
Psychologists rely on in-depth analysis of
the patients while formulating ideas about
personality
Helped behaviorists to illustrate:
Various aspects of their theories
Effectiveness of their therapies
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Limitations of Case Study
Method
Generalizing from a single individual to other people
Determining cause-and-effect relationships with the case
study method
Interference of investigator's subjective judgments with
scientific objectivity
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Strengths of the Case Study
Method
Offers insight into the richness of a person's life
Valuable for generating hypotheses about the nature of human
personality
Acts as a useful research tool
Appropriate in examining a rare case
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Strengths of the Case Study
Method
Suitable for arguing that the individual being studied is normal on
the dimensions of interest
Illustrates a treatment
Demonstrates possibilities
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Statistical Analysis of Data
Types of statistical tests appropriate for
different types of data and research designs
Analysis of variance
Chi-square test
Correlation coefficient
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Statistical Analysis of Data
Statistical significance
The difference between two averages is large
enough to consider that it was not caused by
chance but reflects a true difference between
two observations
Size of the difference is indicated through statistical
values known as effect size indicators
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Statistical Analysis of Data
Correlation coefficients
Statistical test that helps understand the
relationship between two measures
Statistical data is reduced to a single number
that ranges from 1.00 to -1.00
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Figure 2.3 - Three Possible Relations
Between Loneliness and Depression
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Reliability
Extent to which a test measures consistently
Determined by calculating test-retest reliability
coefficient
Factors contributing to poor consistency
Vague test questions or scoring procedures
Fluctuation in response due to taker’s mood
Internal consistency
All items on the test measure the same thing
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Reliability
Internal consistency coefficient
High coefficient indicates that most of the items
are measuring the same concept
Low coefficient suggests items are measuring
more than one concept
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Validity
Extent to which a test measures what it is
designed to measure
Easy to determine for some kinds of tests
Face validity
Way to decide whether a test measures what it
says it measures is to look at the test items
Less certain than with more straightforward
measures
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Validity
Congruent validity
Extent to which scores from the test correlate
with other measures of the same construct
Otherwise known as convergent validity
Discriminant validity
Extent to which a test score does not correlate
with the scores of theoretically unrelated
measures
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Validity
Behavioral validation
Step in determining the construct validity of a
test
Test scores predicting relevant behavior is
important
Usefulness of the test must be questioned if test
scores cannot predict behavior
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