1 2 Continue with personalitydynamics. We are going to be focusing on today and next
class, within person dynamics, mechanisms and proceses. Why do we not always act
in accord with our personality?Why do people not strictly adhere to the traits they
have. People seem surprinsgly and substantiallydifferent from the traits they report.
Semi random sampling of trait terms. There terms, like many, focus on what someone
is like in general. How they typically behave or think or feel. Characteristic of
personalitypsychology in general. We are preoccupiedwith understandingwhat
people are like in general. How people behave on average. What are you like on
average. What mean levels to people show in their thinking,in their feelings, in their
behaviours.Mean levels, average tendencies they show.
We use these terms as they make reference to average levels
Say someone is trusting,you say they are on average more trustingthan others.
Fragile? Labile? Erratic? Percetly good descriptors for thinking,feeling and behavior.
But they do not make reference to what people are like on average. To say someone
is fragile odesn’t mean they break frequently,instead in average circumstances they
are more likely to break. Erractic is a description not of behaviour,but of how erratic
their behavior is. How variable people are? Worthwhile to understandthat people are
variable?Not just the typical levels that people show. After all people are variable.
3 William fleeson: risen to the rank of presidentin personality research. Outlined a set
of principles for how we engage in research to explore intraindivdual varability.
They have historically been definedby mean levels. Trait = mean of someone’s
But fleeson has argued that we need to overturnthis focus, need to focus on not just
typical behaviours,but full spread.Other element’s of people’s behaviour as well. Not
Broad claims, not hypothesis
1) Even though it is likely the case that someone’s typical level of behaviourdiffers
from other, it is the case that this idnividual may show more of a characteristic,
and less of a characteristic across time. So each indvidual will express every level
of a trait over time. Scale 1 -7. sometimes you will be a 4, 4 may not describe you
equally well in all circumstances. It may happenmost of the time, but there might
be ocassions where the person reports a 5,6 or 7. the same individual who
orignially described tehsemelves as 4, may on other ocassions be higher or lower.
Situationsrequire us to change our behaviour.Over time, our behaviourvaries
around a central tendency.Given a sufficent numberof observations, people
make use of the entire range of a scale. People’s reports can be described with a
density distribution.Sometimes more talkative than usual, soemtimes less
talkative than usual. Not one trait, not one person. But all traits, and all people
2) The mean is still the most important, most stable, most predictable characteristics
4 of all of psychology. The mean is one parameter, but not the only parameter.
3) The mean is not the only way, there are other paramaters.Should not equate
traits with the means of traits. Reconceptualize traits as not just the mean, but all
the paramaters from which you can describe a distribution.Understandand
explore how stable and how meaningfulare these other density distrubtionsof
traits and states.
Need to know the concept of a trait.A state. (today we use state and behaviour
interchangeably)both are distinct from traits. Traits express themselves in
behaviours.Being in a particular state or showing a behaviouris the expression of at
rait. Trait is what someone is like in general. State or behaviouris over a narrow
period of time.
Differ from one situation to the next because of many variables.
4 Paper focuses on 3 studies, lecture today focuses on the first. Studies 2 and 3 are
qualifications on the first study.
Importantto know why study 2 and 3 were conductged, but the substitive results are
reportedin the first study.
Explore how well we can describe people’s behaviours using density distributions.
We can describe the state you are in right now using the same words to describe your
We can use the same scale for assessing a trait of an indvidualto assess their state.
(in general vs past hour)
Fleeson collected multiple state records. Records states as they go about the day.
Complete them mutliple times daily to assess how their states vary from one
moment to the next along the big 5 dimensions. Mutiple records of behavioursand
how the big 5 have been expressing htemselves over circumscribed periods of time.
Vertical axis = how frequentlya state has been reported.The curve describes
distribution of frequencies
Frequency dsitribution = density distribution.
The universe is normal for some reason.
5 Density distributioncan be summarized with 3 or 4 paramaters.Location, size, shape.
The mean tells you typically where the scores are generally clustered. Ususally most
importantthingto know. Know the average. Mean is imperfect distributionhowever.
There is typically some or a lto above, ro some beloew
Look at the size or standarddeviation.How much spread or how much diversion
there is around the mean. The standarddeviationof how badly a job the mean does
in describingthe distribution.A smaller standarddeviation means that the central
tendency is a good indicator of the distribution.
Skewness. Where the distribution is shifted to one side of the scale or another side of
the scale. Is the distributionlop sided? If yes, then it is skewed. Violation of
symmetry. If the distributionis not symmetrical, it is skewed. How peaked or shallow
is it? Is the distributionmore peaked than the other? Kurtosis. Kurtosis and skew
describe the shape
Skew describes lopsided to the left or right
Kurtosis describes the peak or shallowness.
Location size shape, skew, kurtosis. This is how we describe traits. Historically just
concentrated on traits. But maybe we can learn about people from the spread of
their behaviour and the shape that it takes.
6 May or may not be the case where we need these paramaters to describe
Left: distribution roated 90 degree. Their staes of extraversion over time, for 3
indviduals.What’s importantto see is how non-overlappingthese distributions are.
Very few occasions where person 2 behaves similarly to person 1 or person 3. 3
doesn’t behave much like 1 or 2 either. Etc. all we really need for this one is the
mean. Person 1 is more extraverted on average than person 2, person 3. person 3
more extraverted than 3. etc. we do not actually need more than the mean. Very little
within person variation.Most of their behaviourindicates their average. Vey little
variablitiywithin the person.
Right: Some of these distributions are more skwed, they differin how kerutotic they
are as well. To describe these 3, we need more than the location of their
distributiosn.Need their size and shape as well. There is so much in person variabiltiy,
so they now overlap.Much less infomration to just know the location of these
distributions.Need to know how they differin terms of size and shaep of
Which one of these hypothesized sitautions are more close to real life? If left is the
closest real life, then we can just focus on the locaiton or average. If right is closer to
real life, then we need size and shape of distribution as well.
7 5 outcomes would support that psychologists need to redfine personalitytraits. Not
1) Within person variability.If we need more than the mean, there has to be
substatinal variabiltiy.Have to have people that differ a lot.
2) Momentary states are not that predictable. Needs to be little resemblance from
one day to the day. Single state indices are notoriously unreliable.Shouldn’t
correlate well. Measure someone on one ocassion then measure on another
ocassion, there should be variability.Single states of behaviour should not show
high levels of consistency.
3) The mean of the distributionwould be very stable. Average level of behaviour is
likely to be very stable. Its frequentuse of perosnality characteristics.
4) But one of the other parmaters should also be stable. His goal needs to be to
show that not just the mean is stable, at least one other feature of the density
distribution should be stable as well. Liberal test and conservative test: liberally
he only needs to show that one other paramter is stable. More conservatively, he
would need to show that all other paramaters are stable as well. There is some
leeway here. At the very least he has to show that one other paramter is stablke.
At the very most he has to show that all other paratmters are stable.
5) The variabilitythat people show has to be meangiful.Cannot be simply error or
nusiance factor. Cannot be osmoen randomlypicking numbers. Has to be
something meanfiul as to why you are picking different numbers on different
8 ocassions to show how you behave.