Types of relationships
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Types of Relationships. Social scientists are interested in discovering functional relationships between variables. In particular, researchers look for: correlations (association, covariation) among vaariables differences between groups or conditions. The nature of causation.

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Types of Relationships

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Types of relationships

Types of Relationships

  • Social scientists are interested in discovering functional relationships between variables.

  • In particular, researchers look for:

    • correlations (association, covariation) among vaariables

    • differences between groups or conditions


The nature of causation

The nature of causation

  • Cause-effect relationships--causation is always inferred, never directly observed

  • “functional” relationships

    • one thing correlates with, or is associated with another (correlation)

    • one thing predicts or explains the amount of variance in another (analysis of variance)

    • one thing has a direct effect on another (path analysis, multiple regression)


Graphic representations of relationships

Graphic Representations of Relationships

(dependent

variable)

Note: “3/4 rule”

the convention is

to make the Y axis

3/4 of the length

of the x axis

Y-axis

(independent variable)

X-axis


Correlations

Correlations

  • displaying correlations using a scattergram

  • linear relationship

    • can be positive or negative

  • curvilinear relationship

    • also known as nonmonotonic relationships, quadratic trends, “u-shaped” or “inverted-u”

    • requires a minimum of three levels of the variable being investigated

  • no correlation

  • spurious effect


Do employees who drink a lot of coffee take more bathroom breaks

Do employees who drink a lot of coffee take more bathroom breaks?


Illustration of scatterplots

Illustration of Scatterplots

  • Scatterplots that are closer to a straight line have correlations closer to +1.0 or -1.0

  • Must have interval or ratio data

  • Correlation does not prove causation


Linear versus curvilinear relationships

Linear versus curvilinear relationships

Linear relationship

Curvilinear relationship


Differences between groups or conditions

Differences Between Groupsor Conditions

  • main effect (changes produced by one independent variable alone)

    • one-way interaction

  • interaction effect (changes produces by independent variables acting together, or in concert

    • two-way interaction

    • three-way interaction


Interpersonal touch social labeling and the foot in the door effect

touch

no touch

interpersonal touch, social labeling, and the foot-in-the-door effect

positive

FITD

.15

.40

negative

FITD

.45

.25


Communicator physical attractiveness and persuasion

communicator physical attractiveness and persuasion

attractive criminal

unattractive criminal

swindler

4.35

5.45

2.80

5.20

burglar


Non significant interaction

non-significant-interaction

A characteristic feature of non-significant interaction effects is that the lines are parallel, or nearly parallel


Potentially significant interaction ordinal

potentially significant interaction(ordinal)


Potentially significant interaction disordinal or crossed

potentially significant interaction(disordinal or “crossed”)


Potentially significant interaction ordinal1

potentially significant interaction(ordinal)


Illustration of an interaction effect

Illustration of an interaction effect

evidence quality

low high

high quality

evidence

Source Credibility

low high

Attitude change

0 1 2 3 4 5 6 7

low quality

evidence

low high

Source Credibility


Illustration of an interaction effect1

Illustration of an interaction effect

Easy test

Test score

0 10 20 30 40 50 60 70 80 90 100

Hard test

500

900


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