Transcript Introduction to experimental design

Introduction to
experimental
design
The psychology experiment
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Predict the causal effect of one thing on another
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Keep everything constant other than the affecting
thing
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Vary the affecting thing systematically
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Measure changes in the affected thing
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Assess statistically whether or not the predicted
effect has occurred
Within participants
same participants in each condition
 controls for individual differences
 introduces order effects and carry-over
effects
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Overview
 Between
participants
 different participants in each condition
 no order effects
 Individual differences
 need to match or randomise allocation of
participants
Mixed design
Mixed design
 some conditions have different
participants, some have the same
Example
- between subjects design
 Comparing
the number of errors made
entering into a computer spreadsheet for
a sample of people listening to loud
popular music with the number of errors
made by a different control sample
listening to white noise.
 Two
different people are compared
Example
within-subjects design
 Studying
the number of keyboard errors
made by a group of 20 secretaries,
comparing the number of errors when
music is played to when music is not
played.
 Performance
of one group of people is
compared in two different circumstances
Why distinguish
 We
need to choose the appropriate
statistical test:
 Between – unrelated or uncorrelated t –
test
 Within - related or correlated t-test
Why laboratory research ?
 Practicalities:
equipment/apparatus to bulky,
security, expensive
 Experimental control: keeping all factors the same
 E.g. light, temp, noise, arrangement of equipment
 These
are extraneous or environmental factors
True or randomised
experiment
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Experimental manipulation: manipulated variable
= independent variable
e.g. Alcohol
Alcohol increases the number of mistakes
The level/amount of alcohol = IV
Amount given to each subject is constant for
each condition
Condition one = 8ml and condition two = 16ml
Lower quantity of alcohol = control condition
Higher quantity of alcohol = experimental
condition
Full population of interest
Randomly
assign into
control and
experimental
groups
Experimental group:
exposed to independent
variable: view violent film
Control group:
View nonviolent film
Checks on experimental
manipulation
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Experiment on memory and anger
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Researcher says pre-scripted offensive comments
to people in the experimental group and nice
things to the control group
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Possible problems:
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View it as a joke, patronising
Resolve the issue by either:
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get subjects to complete of questionnaire on their
mood
after debriefing ask how they felt about the researchers
questions
Pilot
Standardisation of procedures
Keeping things constant
Alcohol and error experiment
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Time of day
Body weight of participants
Time they ate
Researchers behaviour
Any others ?
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Tape recorded instructions
Come into lab previous day
Resolutions
Randomisation
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Who goes in the experimental or control group
What if the participant undergoes more than one
condition
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Toss of a coin
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Throw of a dice
Write on cards, random number tables, computer
number generation
more than two
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Problems: runs of the same condition or number of
participants in either condition is different
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Randomisation ensures that there is no systematic
bias in the selection process of participants,
although chance factors may lead to differences
between the conditions.
Matching
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Ensuring equal numbers
Matched block or block randomisation
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First Ss of a pair is randomly assigned to control
condition using the specified procedure, while
other pair is assigned to remaining condition
We need to ensure that participants in the
control and experimental condition are similar
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Matching on gender, age weight
Pre-test and post test sensitisation
effects
Number Of
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Without a pre-test
errors
there is only a
14
measure of people
Performance after
10
drinking
But, look at the pre6
test – maybe due to
randomisation
people who
2
generally made
more mistakes were
in the 8ml group
8ml
16ml
pre-test
post-test
Cont…
 Having
a pre-test helps us to determine
whether randomisation worked
 It allows us to see whether or not there has
been a change in performance between
the pre- and post test
 Disadvantage
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Alert the Ss to the purpose of the experiment
 Solutions
 Increase
the length of intervals between
the pre and post test
 We could test participants again after the
post test
Within-subjects design
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Fatigue or boredom – number of mistakes
maybe more in the second than in the first
condition
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Practice effect – Ss become better at task
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Carryover, asymmetrical transfer – the effect
of an earlier condition affects the subsequent
condition. Solution increase time between
conditions, but the problem is sometimes they
just don’t come back !!
statistical significance
 The
key to determining if a treatment had
an effect is to measure the statistical
significance.
 Statistical
significance shows that the
relationship between the variables is
probably not due to mere chance and
that a real relationship most likely exists
between the two variables.
Statistical significance is often represented
like this: p < .05
Cont….
A
p-value of less than .05 indicates that
the possibility that the results are due
merely to chance is less than 5%.
Occasionally, smaller p-values are seen
such as p < .01. There are a number of
different means of measuring statistical
significance. The type of statistical test
used depends largely upon the type of
research design that was used.
Androgyny
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Androgyny
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Today we accept a lot more diversity (e.g. Hayley
Cropper off Corrie) and see gender as a continuum
(i.e. scale) rather than two categories. So men are
free to show their “feminine side” and women are
free to show their “masculine traits”.
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For example,
• Beckman wears a skirt
• Earrings for men
• Women’s boxing
• Girl Power
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So it has become a lot more difficult to say what us
typically “male” or “female”, and people who are
biologically one sex often possess qualities (and the
behaviour) appropriate to the opposite sex.
Androgyny
 Refers
to the recognition that individuals
possess qualities (or traits) which are
characteristic of both masculinity and
femininity (Bem, 1974)
 Davison
(2000) - women that those who had
androgynous characteristics scored highly in
terms of their well-being, than women that
were not androgynous.
 Gana
(2001) found that highly androgynous
husbands had a happier home life and
participated more in the household tasks and
in the bringing up of the children than did
husbands with rigid traditional gender views.
Questionnaire
 Take
10 minutes to complete this
questionnaire and score it.
 Do
not identify yourselves on the
questionnaire
Lets do your first psychological experiment !!!!
We will use these results for our seminar session
next week, and create a discussion section
ourselves during the seminar session. I will
provide you with the introduction and
methods sections.