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BAILEY CHAPTER 3
TYPES OF RELATIONSHIPS
Bivariate relationships:
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Strenght of relationships
Positive vs. negative relationships
Symmetrical rel.
Asymmetrical rel.
Linear vs. curvilinear
Spurious
intervening
Supressor
Specification variable
Strenght of relationship:
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After we have established that two
variables are indeed related the next
question is how strongly they are
related. İf two are related then we can
predict the change in one looking at
the change in the other.
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The degree to which a prediction is
correct (out of 100 predictions) is
called strenghth of a relationship.
Common stat for this is correlation., or
Pearson’s product moment correlation
coefficient. Varies between -1 and 1.
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SYMETRİCAL VS. ASYMMETRİCAL
RELATİONSHİPS
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Symmetrical—change in one variable is
asssociated with change in the other
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In asymmetrical change in one variable is
accompanied by change in the other but not
vice versa. Smoking and cancer.
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It is common in statistical lit to equate
symmetrical relationships with explanation
and asymmetricla relations with prediction.
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İce cream eating ---- glove wearing
(symmetrical)
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Divorce-- number of cars sold
(symmetrical)
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alternative indications of the same variable
part of a common system
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Asymmetrical:
 smoking- lung cancer
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gender -- tv watching
age-learning second language
time order (temporal sequence)
alterability (we know which one is
dependent/independent)
 SPURIOUS
RELATIONSHIP
A
relationship which two variables appear to
be related only because a third variable is
causing the occurence of both.
Employment
tv watching
education
 Nationalism
conservatism
parenting style
Intervening relationship:
Variables A and B might be highly correlated
because A might cause C, and in turn C might
cause B.
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Sex
tv watching
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less hours of work
SUPRESSOR VARİABLES:
Two variables appear to be unrelated because aech is correlated with a third variable which
supresses the relationship between the two other variables. It suppresses the relationship by
being positively correlated with one of the variables and negatively correlated with the other.
The relationship will appear when third variable is controlled.
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Education
income
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Age
Low age pulls education up, but income down.
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Education
fertility
+
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İncome
SPECİFİCATİON VARİABLE:
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Native language
academic
Success
gender is the specification variable.
CONCEPT OF CAUSALITY
 Associaton vs. causation.
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X causes Y if;
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there is relation between X and Y.
Asymmetrical
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a change in X results in a change in Y
regradless of other factors.
3 combinations:
Necessary but not sufficient:
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X is necessary but not sufficient for the existence of Y.
Flour is necessary but not sufficient to bake a cake. We need
other ingredients.
X must occur before Y occurs, but X alone not enough to
cause Y.
Chemical makeup __________ depression
sufficient but not necessary
X and Z are alternative causes of Y. Not partial causes.
Each is sufficient to cause Y by itself, but they are
alternatives.
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High speed ___________________traffic accident
Drunk driving _________________traffic accident
X is both necessary and sufficent simultenously for Y.
 Y will never exist unless X exists, and will always exist
when X exists. X is the complete and the only cause.