Preference And Familiarity Preference And Familiarity For Male ForenamesFor Male Forenames

Jonathan Stirk & Jasper RobinsonJonathan Stirk & Jasper Robinson

E-mail: E-mail: jas@psychology.nottingham.ac.ukjas@psychology.nottingham.ac.ukjwr@psychology.nottingham.ac.ukjwr@psychology.nottingham.ac.uk

IntroductionIntroductionIntroductionIntroduction

AimsAims To be introduced to the area of psychoaestheticsTo be introduced to the area of psychoaesthetics To develop a greater understanding of partial To develop a greater understanding of partial

correlation and linear regressioncorrelation and linear regression To learn more about design and control of To learn more about design and control of

experimentsexperiments ObjectivesObjectives

Over the next two sessions you will design and Over the next two sessions you will design and conduct a study in an attempt to predict conduct a study in an attempt to predict participants’ preferences for certain male participants’ preferences for certain male forenames over othersforenames over others

IntroductionIntroductionIntroductionIntroduction

Organisation of this sessionOrganisation of this session What is psychoaestheticsWhat is psychoaesthetics Previous researchPrevious research How to finish the design of your own studyHow to finish the design of your own study Run the experiment (between now and the Run the experiment (between now and the

next session)next session) Next session – how to analyse and write up Next session – how to analyse and write up

the report (plus trouble shooting for those who the report (plus trouble shooting for those who still need to test subjects)still need to test subjects)

What Is Psychoaesthetics?What Is Psychoaesthetics?What Is Psychoaesthetics?What Is Psychoaesthetics?

Psychoaesthetics is the experimental Psychoaesthetics is the experimental study of why people like certain things, study of why people like certain things, and dislike others. - (Berlyne, 1971, 1974)and dislike others. - (Berlyne, 1971, 1974)

One theory suggests that familiarity is One theory suggests that familiarity is directly and positively related to liking… - directly and positively related to liking… - (Zajonc 1968; Harrison, 1977)(Zajonc 1968; Harrison, 1977)

……Despite contrary evidence that Despite contrary evidence that familiarity can breed contempt. - (Cantor & familiarity can breed contempt. - (Cantor & Kubose, 1969)Kubose, 1969)

Familiarity And LikingFamiliarity And LikingFamiliarity And LikingFamiliarity And Liking

Children’s preferences for letters in a Roman Children’s preferences for letters in a Roman alphabet rather than a Cyrillic alphabet waned with alphabet rather than a Cyrillic alphabet waned with increasing age (despite increasing familiarity with increasing age (despite increasing familiarity with the Roman alphabet). the Roman alphabet). This lead researchers to suggest that the relationship This lead researchers to suggest that the relationship

between familiarity and liking was akin to an inverted U.between familiarity and liking was akin to an inverted U. (Slukin et al., 1973).(Slukin et al., 1973).

Other studies demonstrated that the relationship Other studies demonstrated that the relationship between familiarity and liking was diminished as age between familiarity and liking was diminished as age increased – further evidence for an inverted U.increased – further evidence for an inverted U. (Colman et al., 1975).(Colman et al., 1975).

Monotonic Or Non-monotonic?Monotonic Or Non-monotonic?Monotonic Or Non-monotonic?Monotonic Or Non-monotonic?

FAMILIARITY

LIKING

Familiarity And LikingFamiliarity And LikingFamiliarity And LikingFamiliarity And Liking

One criticism of these studies is that the One criticism of these studies is that the stimuli lacked ecological validity. How stimuli lacked ecological validity. How much can anyone like the word “CHAIR”?much can anyone like the word “CHAIR”?

In response to this criticism Colman, In response to this criticism Colman, Slukin and Hargreaves (1981) decided to Slukin and Hargreaves (1981) decided to look at first names and surnames. look at first names and surnames. Very familiar surnames (e.g. Smith) and very Very familiar surnames (e.g. Smith) and very

unfamiliar surnames (e.g. Bodle) were not unfamiliar surnames (e.g. Bodle) were not liked. Names of medium familiarity were like liked. Names of medium familiarity were like most – supporting the inverted U.most – supporting the inverted U.

Inverted U Or Straight Line?Inverted U Or Straight Line?Inverted U Or Straight Line?Inverted U Or Straight Line?

BUT first names displayed a positive monotonic BUT first names displayed a positive monotonic relationship, reflecting Zajonc’s early theories.relationship, reflecting Zajonc’s early theories.

Why do some studies suggest an inverted U Why do some studies suggest an inverted U whereas other studies (albeit fewer) suggest a whereas other studies (albeit fewer) suggest a straight line relationship?straight line relationship?

You will test the less accepted of these two You will test the less accepted of these two theories – that of the linear relationship. Is there theories – that of the linear relationship. Is there another variable that may account for the another variable that may account for the relationship between familiarity and liking? Can relationship between familiarity and liking? Can we predict liking on the basis of familiarity or on we predict liking on the basis of familiarity or on the basis of some other variable?the basis of some other variable?

The ExperimentThe ExperimentThe ExperimentThe Experiment

Two E-prime programs – ‘BlockedNames.es’ and Two E-prime programs – ‘BlockedNames.es’ and ‘RandomNames.es’ ask for familiarity and liking ratings ‘RandomNames.es’ ask for familiarity and liking ratings on a 1-5 scale. on a 1-5 scale.

Choice of program depends on your choice of design.Choice of program depends on your choice of design. Do you ask all the familiarity questions first and then the liking Do you ask all the familiarity questions first and then the liking

questions (BlockedNames), or do you mix the liking and questions (BlockedNames), or do you mix the liking and familiarity questions in one big random block (RandomNames)?familiarity questions in one big random block (RandomNames)?

Between groups or repeated measures? Between groups or repeated measures? If one person answers both questions to all the names will they If one person answers both questions to all the names will they

guess the hypothesis? If the questions are asked to separate guess the hypothesis? If the questions are asked to separate people, will individual differences in familiarity with names affect people, will individual differences in familiarity with names affect the results?the results?

The ExperimentThe ExperimentThe ExperimentThe Experiment

What names should you use? Where will you find these What names should you use? Where will you find these names? Will you choose them on a random basis? Or names? Will you choose them on a random basis? Or from a previous study? How many will you use (the from a previous study? How many will you use (the programs are set up for 10 – you may need considerably programs are set up for 10 – you may need considerably more)?more)?

Choose a third variable. What other factor do you think Choose a third variable. What other factor do you think may influence familiarity. This third variable should be may influence familiarity. This third variable should be something that subjects can mark on the same 1 to 5 something that subjects can mark on the same 1 to 5 scale as familiarity and liking. scale as familiarity and liking.

E.G. How familiar is the name MARK? How much do you E.G. How familiar is the name MARK? How much do you like the name MARK? like the name MARK? Do you know many people called Do you know many people called MARK?MARK?

What You Need To Do This WeekWhat You Need To Do This WeekWhat You Need To Do This WeekWhat You Need To Do This Week

Get into groups of threeGet into groups of three Familiarise yourself with the two programs (but Familiarise yourself with the two programs (but

you cannot use your own data in your study!)you cannot use your own data in your study!) Write down your experimental designWrite down your experimental design

Which subject does what, how many names, what Which subject does what, how many names, what should be random, (use the experimental checklist should be random, (use the experimental checklist from last session) etc.from last session) etc.

On the basis of your design modify the e-prime On the basis of your design modify the e-prime experiment appropriately (ask for help if you get experiment appropriately (ask for help if you get stuck) – but save under a stuck) – but save under a differentdifferent name name

Decide where to get your stimuli from, and then Decide where to get your stimuli from, and then go get themgo get them

What You Need To Do Before The Next What You Need To Do Before The Next SessionSession

What You Need To Do Before The Next What You Need To Do Before The Next SessionSession

Put all the names into your programPut all the names into your program Pilot the experiment on friends (these pilot Pilot the experiment on friends (these pilot

subjects can know already about the hypothesis, subjects can know already about the hypothesis, but cannot be used in the final analysis)but cannot be used in the final analysis)

Modify the experiment if it did not run according Modify the experiment if it did not run according to plan with your pilot subjectsto plan with your pilot subjects

Run the experiment on as many subjects as you Run the experiment on as many subjects as you stipulated in the design phase. All real subjects stipulated in the design phase. All real subjects should be naïve, where ever possible, especially should be naïve, where ever possible, especially in a repeated measures designin a repeated measures design

In The Next SessionIn The Next SessionIn The Next SessionIn The Next Session

In the next session you willIn the next session you will Calculate mean ratings across items (rather than Calculate mean ratings across items (rather than

subjects)subjects) Correlate familiarity, liking and your own variable to Correlate familiarity, liking and your own variable to

produce a correlation matrixproduce a correlation matrix Perform partial correlations to find the strongest Perform partial correlations to find the strongest

relationship with liking for male forenamesrelationship with liking for male forenames Calculate a simple linear regression to note whether Calculate a simple linear regression to note whether

liking can be predicted by the strongest related liking can be predicted by the strongest related variable from the partial correlationvariable from the partial correlation