Investigation of the Availability Heuristic in the Estimation of the

 Investigation of the Availability Heuristic in the Estimation of the Frequency of Names IB HL Psychology IA Sample 4 Table of Contents
Abstract
Introduc tion
Method
Results
Discussion
Work Cited
Appendix i - Standardized Instructions
Appendix il - Informed Letter of Consent
Appendix ill - Debriefi ng Notes
Appendix iv - List 1: 20 More Famous Names and 17 Less famous Names
Appendix v - List 2: 17 More Famous Names and 20 Less Famous Names
Appendix vi - Raw Data
Appendix vil - Mann Whitney Test Calculations
Abstract
According to Tversky & Kahneman (1973), av ailability heuristic is a circu
which people estimate the frequency of an event, or the amount of somet
class, based on how easily an example can be brought to mind. The aim of
experiment was to test if the availability heuristic has an effect on the partici
ability to estimate the frequency of famous or not so famous names written on
It was hypothesized that the availability heuristic will have an affect on the
participants' ability to estimate the frequency of famous or not so famous nam
on lists given. The design was independent measures design and the partit
(N=12) were chosen using the opportunity sampling method. Group 1 ha(
20 More Famous names in and 17 Less Famous names read aloud to them
2 had a list of 17 More Famous names in and 20 Less Famous names read
them. The independent variable of this study was the number of famous ve
famous names read out from lists to the participants. The dependent variable
study was the list that was estimated as having a larger amount of names on it
or not so famous.
A Mann Whitney test was used to determine the significance of the result
results showed that the information was not signifi cant because our reall
support the hypothesis. Therefore the null hypothesis was retained and we
conclusion that availability heuristic does not have an effect on one's ability t(
the frequency of More 'Famous or Less Famous names that were read aloud frt
Word Count: 280
A. Introduction
Availability heuristic is a human cognitive bias when people predict the frequ,
event, or a quantity within a population, based on how easily an example can I
about. It can cause one to overestimate probabilities of events that are associat
memorable or vivid amounts. Due to these memorable events being overstate(
coverage in the media, the bias is intensified in society. Two examples of this
probability of plane crashes and the kidnapping of children, both of which are
but due to the amount of media coverage on incidents relating to them, big ma
the people overestimate their probability and therefore behave consequently.
Av ailability heuristic was first shown in a study conducted by Tversky & Kahl
1973 they researched J u d g m availability
ent
investigate
bias in judgments about lists of names. In their experin
presented
4
-u n d elistsr to the participants. Two of the lists had 19 famous women an
famous
u n cmen
e on
r them,
t a and the other two lists had 19 famous men and 20 less h
-wi omen.
n t With
y : the use of a between-groups design, which describes the statistic
comparison
h
e
u of two
r or
i more different groups of subjects that are focused on difi
experiences
s
t
i orctreatments, the first group was asked to recall as many names a!
and
a the second
n group was asked to estimate what was more frequent, famous n
less
d famous names. The results gave a two-fold implication. To begin with, the
that
b the famous
i
a names were most easily recalled compared to the less famous
Additionally,
s
e
despite
s
the fact that the less famous names were more frequent, t,
majority
of the participants estimated that the famous names were called more
"
This
i shows that a key factor that emerged from this study is that although the a
heuristic
n
serves as an effective strategy in many situations, leading to accurate,
they
o can also lead to 'systematic errors', especially when judging frequency.
r
Another study on availability heuristic was a study by Schwarz et al (1991), in
they had participants describe examples of behavior, either very assertive or ve
unassertive, behaviors in which they acted out in different role-playing scenari(
participants were also asked to describe either 6 or 12 examples of assertive or
unassertive behavior. Afterward the participants were asked to rate their own
assertiveness. The results showed that the participants rated themselves as bein
assertive after describing 6, instead of 12, examples for an assertive behavior c(
and rated themselves as being less assertive after describing 6, instead of 12, ex
unassertive behavior. The study showed the implications of recalled content we
qualifi ed by the ease with the personal content that could be brought to mind.
Chapman & Chapman (1967) conducted a study, in which they described a bias
judgment of the frequency in which two events co-occur. Their study showed tl:
occurrence of a paired distinctive stimuli resulted in an overestimation of the fr(
of certain pairings. In order to test this theory, judges were presented with infori
that concerned several hypothetical mental patients. The data for each patient cc
a clinical d i
111
drawing. The participants clearly overestimated the frequency of co-occurren(
connections, such as suspiciousness and peculiar eyes. This effect was labelec
correlation". The strength of the associative link between the two events conic
the basis for one's judgment of how frequently the two events co-occur. Whei
association is strong, one is more likely to conclude that the events have been
frequently. Therefore, strong associates will be estimated as having occurred t
frequently.
Aim: The aim of this experiment is to test if the availability heuristic has an at
participants' ability to estimate the frequency of famous or not so famous nam
on lists given.
Hypothesis: Av ailability heuristic will have an affect on the participants' abilli
estimate the frequency of famous or not so famous names written on lists give
Null Hypothesis: Av ailability heuristic will not have an affect on the participai
to estimate the frequency of famous or not so famous names written on lists gi
B. Method: Design
The type of design we have chosen for our experiment was an independent me,
design. We had to conduct the experiment on two different groups, both under
conditions. The advantage of using an independent measures design is that it
keep the validity of the results high, even though we have a small number of gi
Controls that we have undertaken to avoid confounding variables are making s
do not explain what we are looking for before the experiment is started, readinl
names from the list instead of giving it to the participants, and conducting the e
on two separate groups to avoid the expectancy effect. The independent variabl
experiment is the number of famous versus not so famous names read out from
participants, and the dependent variable is the list that was estimated as having
amount of names on it, famous or not so famous. Ethical guidelines were met b
the participants a letter of consent before the experiment and by debriefing ther
rules and instructions of the experiment.
C. Method: Participants
In our experiment we had two groups of 12 students; all were between the ages
18. In group I, which we read the list of 20 More Famous names and 17 Less F
names (see app. iv) to, there were three males and nine females, nine of the stuc
group I were non-native English speakers, and in group 2, which we read the li!
More Famous names and 20 Less Famous names (see app.v) to, there were six
six females, nine of the students were non-native English speakers. Our particip
made up of multicultural, multilingual students that all came from an internatioi
We used opportunity sampling because the sample was already given to us base
when we were avniinhie Thp d v n t n a
would be made up of a lot of the same kinds of people, for example, all the pe
sample were students between the ages of 16 — 18. In order to decide which gi
which list, we fl ipped a coin and it was decided that group I would have list I
consisted of 20 More Famous names and 17 Less Famous names read to them
2 would have list 2, which consisted of 17 More Famous names and 20 Less
names, read to them.
Materials
- 2 5 pieces of paper
- 2 5 pens
25 copies of the letter of consent for the participants to sign (appet
- L i s t 1 (see appendix iv)
- L i s t 2 (appendix v)
D. Method: Procedure
Kahneman & Tversky (1973)
1) D iv id e participants into two groups of 12 assigning the participants intc
and 2.
2) A s k participants to sign consent forms (see appendix ii)
3) Dis tribute paper and pen to participants.
4) Read aloud list 1 to group I (see appendix iv)
5) Read aloud list to 2 to group 2 (see appendix v)
6) A s k group 1 to estimate which category has more names in it, more fan
less famous, and write estimation in figures on their paper. The particip
have 1 minute to do so.
7) A s k group 2 to estimate which category has more names in it, more fan]
less famous, and write estimation in figures on their paper. The particip
have 1 minute to do so.
8) Collec t papers from participants.
9) D ebr ief participants by explaining them the purpose of the experiment,i
them for participating, and let them know that once the results are calcu
w ill be available for their viewing. (see app. iii)
E. Results: Descriptive
Table 1. The Means and Standard Deviations '
Mean
Standard
Deviation
Group 1
More Famous
Less Famous
Names
Names
19.58
14.25
8.59
6.92
Group 2
More Famous
Le
Names
16.83
4.75
Figure 1.
w o n ttumabom K y v e t Wotv NoovivoA q•ovi op t i r
o
,
i
•
The Level of data used was interval (see app. vi for raw data). The mean gives
average number, and standard deviation shows you how far away it is from the
Table 2 shows that the mean of group 1 More Famous names was 19.58, the m(
group 2 More Famous names was 16.83; the mean of group 1 Less Famous nan
14.25, and the mean of group 2 Less Famous names was 16.30. The standard d(
group 1 More Famous names was 8.59, the standard deviation of group 2 More
names was 6.92, the standard deviation of group I Less Famous names was 4.7.
standard deviation of group 2 Less Famous names was 3.60. The size of the sta
deviation for More Famous names in group I is large compared to the mean, ov
size of the mean. Although most of the numbers range from 10 — 25 there are nt
less as 8 and as large 40, which can throw off the data because they are outliers.
of the standard deviation for Less Famous names in group I is large compared t
mean, it is half the size of the mean, this is because there were numbers ranging
25, many of which were outliers.
F. Results: Inferential
The type of test used to carry out the calculations was the Mann Whitney Tes
vii for Mann Whitney calculations). We used this test because we had an inde
samples design. Because of the size of the sample and the lack of a standard d
of data, the level of data was reduced to ordinal. The U value of 63.5 does not
critical value of 0.05. Consequently, the results are not significant and may be
chance. The null hypothesis is retained. Therefore, availability heuristic will n
affect on the participants' ability to estimate the frequency of famous or not s(
names written on lists given.
F. Discussion
The results show that availability heuristic does not have an effect on the esti'
the frequency of names read from a list. Although the mean in group I shove
majority of the participants guessed that the frequency of the names read fron
-More Famous Names was higher then the list of names read from the list of L
Names, the mean of group 2 showed that the majority of the participants gues
there was a similar amount of names read from both lists. Therefore, with the
Mann Whitney Test, we were able to fi nd out that our information was not sig
In the study conducted by Tversky & Kahneman (1973), their results were sig.]
whereas ours were not. Tversky 8z.• Kahneman were looking at how a class whc
instances are easily retrieved will seem larger than a class of equal frequency v
occurrences are not as easily retrievable. Our experiment did not confirm this t
Tversky & Kahneman also factored gender into their study, this is something ti
out. In order to get more in-depth information, if this study was to be repeated,
should be factored in. In Chapman & Chapman's (1967) study, they asked juc4
associate a mental patient with a drawing, whereas in our study we were asklN
participants to associate names heard with familiarity. Chapman & Chapman f(
there was a clear overestimation of frequency, whereas our results showed othe
Schwarz et al (1991) showed that implications of recalled content were qualifie
familiarity of the content, our results showed that even though one of the lists v
familiar, it didn't help the participants estimate the amount of names in the lists
A confounding variable in our experiment was language. Many of the participa
of 12 in both groups, were non-native speakers, this is because an independent !
design was used and therefore there was participant variability. The language 13
be a problem when trying to understand the names read aloud and the instructio
culture some of the participants might have been more or less familiar with the
the lists. In the future it would be wise to make sure that the sample was only ol
culture.
Based on the results of this experiment, availability heuristic does not have a
one's ability to estimate the frequency of More Famous or Less Famous narr
read aloud from lists.
Wor k Cited:
Anissimov, Michael. "What is Av ailability Bias?" wisegeek. N.p., 9 Sept. 20
- Web. 1 Nov. 2010. <http://www.wis egeek .c om/
, what
isChapman
& Chapman, L. J. (1967). Illusory Correlation in Observational R
a v a of
i Verbal Learning and Verbal Behavior, 6, 151-155.
Journal
labil
i t y - S. (1997). The Av ailability Heuristic: Effects of Fame and Gende,
McKelvie,
bias
Estimated Frequency of Male and Female Names, journal of Social Psycho!,
.
137(1),
63-78. Retrieved from Psychology and Behavioral Sciences Collect
database.
h
t
m
>
.
Appendix i. Standardized Instructions
Welcome. As you were previously informed, you are taking part in a study. F
to the names that will be read aloud by the researchers, and follow the instruct
to you.
Appendix L e t t e r of Consent
,
amw illin g t o takepar ti n this experiment.
am informed and aware of the instructions involved, and the experiment's ai
investigate the availability heuristic when judging a list of names given to a gt
multicultural, multilingual participants depending on the familiarity of the nail
I am aware that I have the ability to withdraw my results at any point in time d
experiment.
I am aware that by participating in this study I will endure no physical or ment
to myself or others.
I am aware that I will be debriefed after the experiment's procedure is carried (
results have been recorded.
Gender:
Are you a native English speaker? Y e s / No
Participant's signature:
Date of experiment:
Appendix D e b r i e fi n g Notes
We would like to thank you for participating in our experiment. We had you
number of names from a list containing famous people names and a list conta
well-known people's names. We wanted you to do this as we were examining
heuristics and wanted to determine if you estimated that there were more nam
of famous people names than the list of less well known peoples names. We fo
there was not a concrete correlation in this study. Thus, we have had to accept
hypothesis of the same frequency of number of words will be estimated for mo
names and less famous names by the multicultural, multilingual group of parti
attending a international school, regardless of the familiarity of the names and
many times they are mentioned. Thank you.
Appendix iv.. List 1 ()I'M More Famous Names and 17 Less Famous Arames
20 famous names
1. Brad Pitt
1
2. Megan Fox
1
1
3. Orlando Bloom
1
4. Kate Hudson
5. Tom Cruise
2
1
1
Penelope Cruz
.
Jennifer Garner
.
George Clooney
5
.
Angelina Jolie
.
Miley Cyrus
6
1
8. Mariah Carey
.
4
1
7. Britney Spears
Ben Affl eck
3
1
6. Nicole Kidman
.
7
8
W i l l Smith
.
Jennifer Aniston
9. Tom Hanks
1
9
.
Will Farell
10. Lil Wayne
2
0
.
Vince Vaughn
17 less famous
1. C hr is Pine
10. Ashely Benson
2. Benjamin Bratt
11. Kelly Rutherford
3. E l l e Fanning
12. Donald Faison
4. Matthew Morriosn
5. C hr is Colfer
13. Kelly Rowan
14. Peter Gallagher
6. D o u g Savant
15. Lee Norris
7. K y l e MacLachian
16. Moira Kelly
8. L i s a Edelstein
17. Carlos Bernard
9. J u lie Benz
Appendix v.
- Lis t
2
20 famous names
o f
1 Brad
7 Pitt
L
M
o
2.
Megan
Fox
r
e
F Orlando
a
3.
Bloom
m
o
4. Kate Hudson
u
s
5.NTom Cruise
a
6. Nicole Kidman
m
7.e Britney Spears
s
8.aMariah Carey
9.nTom Hanks
d
2
17
0 less famous
L
1. Chris Pine
e
s 2. Benjamin Bratt
s
3. E l l e Fanning
F
a 4. Mat t hew Morriosn
m5. C h r is Colfer
o
u 6. D o u g Savant
s
7. K y l e MacLachlan
N
a 8. L i s a Edelstein
m9. J u lie Benz
e
s 10. Ashely Benson
10. Lil Wayne
11. Ben Aftleck
12. Penelope Cruz
13. Jennifer Garner
14. George Clooney
15. Angelina Jolie
16. Miley Cyrus
17. Will Smith
11. Kelly Rutherford
12. Donald Faison
13. Kelly Rowan
14. Peter Gallagher
15. Lee Norris
16. Moira Kelly
17. Carlos Bernard
18. Elisha Cuthbert
19. David Duchovny
20. Evan Handler
Appendix vi:
Table 1: Raw Data for Group 1 and 2 Frequency Estimates of Names in
Group 1
More Famous
13
25
15
20
40
16
30
15
18
15
20
Group 2
Less Famous
8
25
15
15
5
15
20
9
20
17
20
2
More Famous
15
15
21
23
9
18
20
20
15
13
10
23
Less
15
18
17
19
11
21
20
20
10
13
15
17
Appendix vii:
1
Sample A: Group 1 More Famous names
Sample B: Group 2 More Famous names.
Ranks for
1c ount 1 Sample A 1 Sample B
1 R a w Data fo r
1Sample A j Sample B
4.5
IS
2
22
8.5
25
3
8.5
19
2
1
4
IS
16.5
203
20
40
2
3
Critical Values of U fo r rq--12. ntoLevel of Significance for a
Directional Tes t
.05 I . 0 2 5 1 . 0 1
Non-Directional Test
24
2
6
12
U.S
16
18
7
23
16.5
30
8
20
•5
16.5
Ls
20
1l ower limit
1
5
13
1upper limit
9
133
115
18
10
8.5
4.5
15
163
3
-—
20.5
0.
20
12
1
9
1
0
23
1. 0 5
42
102
3 7
1 0 7
. 0 2
I
31
1 1 3