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PSY230H5 Lecture Notes - Trait Theory, Lexical Hypothesis, Factor Analysis

by OC4

Course Code
Ulrich Schimmack

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Chapter Three
Description of Personality Traits:
A. Big Five
- taxonomy
- lexical approach
- extract all personality-relavent terms from dictionary
- Lexical hypothesis: people will invent words for personality traits that have the largest
consequences on their lives. The traits that are important enough will be translated into
all languages. Therefore, the most important traits will have a word in each language. Use
that language’s personality trait lexicon to determine important personality traits.
- go through the dictionary and list all the words. Then they eliminate words that are
rarely used.
- the list is given to participants where they will either rate themselves or a close other on
a scale of how well the adjective describes their personality.
- 4 major categories of words: personality traits, temporary states, higligh evaluative
judments, physical characteristics
o Allport and Odbert (1936):
-18000 words
- eliminated unrelated words (phys charact, momentary sstates, evaluative) ! 4500
o Implicit personality theory
-use people’s perceptions of relatedness to create taxonomies of personality traits
- intuition of which words are related! problematic
o Empirical correlations
- More often, use correlation coefficients as a measure of relatedness.
!The two approaches produce similar results
o Factor analysis
- groups variables
- The variables are put into groups depending on how correlated they are. The traits are
personality traits. So personality traits that are similar are grouped as one factor.
- Factor analysis allows us to summarize the relations among a large number of
variables in terms of only a small number of groups or factors.
- Factors are DIMENSIONS. They are not TYPES. People differ by factor in the way that
they may have different levels of each factor. Represent the persons level of that
dimension through a standard score.
- moderate to strong correlated variables grouped together = Factor I
- SIGNS don’t mater
- weakly or uncorrelated variables kept separate= Factor II
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