Pgs. 25 - 29
 GOAL:
establish cause and effect relationship
between two variables
 Experiment:

Quantitative research (generates numerical data)
 Variables


Independent Variable (IV): variable being
manipulated or changed in the study
Dependent variable (DV): the variable that is
being measured
Variables must be Operationalized, i.e. they
must be measurable.

Operationalize your variables by considering
each of the following descriptions and deciding
whether it is an example of aggression or not.






Two men fight over a parking space
A football player kicks the ball into a goal
Two girls give a boy the “silent treatment” on the
playground
A man kicks the back of the car when it will not start
Three students have a heated debate about whether
global warming is happening.
Know write a well worded definition of
aggression.
The Experimental Hypothesis predicts the
relationships between the IV and the DV
 Null Hypothesis: predicts that there will be no
results or that the results will be due to chance.
 The Control Group has no experimental actions
applied to it.
 WE CAN NEVER PROVE ANYTHING…..WE CAN
ONLY DISPROVE.

Accept the null hypothesis
 Refute the null hypothesis
 Except experimental hypothesis if demonstrate effect
due to IV manipulation.


1.
2.
3.
4.
5.
Identify the IV and DV in each of the experimental
hypotheses:
People are more likely to make a risky decision when
they are in a group than when they are alone.
An increase in carbohydrates decreases ones ability
to concentrate.
People will react more quickly to an auditory stimulus
than a visual stimulus.
Lack of sleep will affect learning new word
negatively.
Children who have watched a film with a model
hitting a blow-up doll will exhibit more aggressive
acts toward a blow-up doll than children who have
not watched the film.
 Laboratory
experiments
 Field experiments
 Natural experiments
 Pros:


Easy to control
Easy to replicate
 Cons



Artificial environment
What is the ecological value?
Would your result stand up outside of a lab
setting?
 Pros





Used in Social Psychology
Takes place in natural environments, but IV is
still manipulated.
e.g. Piliavin and Rodin (1969) helping behavior in
a New York Subway
Kitty Genevese 1964
The bystander effect
 Cons

Cannot control all variables
 Natural
experiment or quasi – the researchers
have no control over the variables



Research on stoke patients
Cannot change gender
Children who have been separated from their
parents due to war

Confounding Variables: undesirable variables that influence the
relationship between the IV and DV.

Artificiality – the situation is so unlikely that one has to wonder if
there is any validity to the study

Three of the most common confounding variables:

Demand characteristics or Hawthorn Effect –
participants behave in a manner that they think they
should to meet the demands of the study.


Researcher Bias or observer bias- the researchers sees
what he wants to see.


To overcome – Single Blind control – participants do not
know what the study is about.
To overcome – Double Blind control – the participants &
researcher do not know who is in the control group vs.
experimental group
Participant Variability – sample represents same
characteristics

Overcome – random sampling
 Not
all experiments can be carried out,
however, data can reveal relationships
between two variables = Correlations
 Correlation – as one variable changes the
other variable changes. This does not mean
there is a cause and effect.


Positive correlation: as X increases Y increases
Negative correlation: as X increases, Y decreases
 Note
– no IV is manipulated, thus there is not
cause and effect.
1. They
are simple and provide a numerical
representations of the relationship that can
be easily understood
2. They allow the study of a number of
variables that cannot be manipulated
experimentally.