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Conducting Empirical Research
Empirical Research: the systematic gathering and analysis
of information.
Preliminary Steps in Empirical Research
1.
Identify a Problem: the research question
2.
Review the relevant literature
3.
Theoretical Considerations: what is the theory? Is
there one?
Theory: an integrated set of statements designed to
account for, predict, and even suggest ways of
controlling certain phenomena.
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Major Steps in Conducting Empirical Research
1.
Develop a hypothesis
Hypothesis: a specific testable proposition about
something you want to study.
A prediction about the relationship between the
relevant variables.
To test a research hypothesis:
a.
Select a phenomenon of interest, and identify
relevant variables
b.
Control and measure relevant variables and
minimize influence of random or irrelevant
variables
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Identifying Relevant Variables
Hypothetical Constructs &
Observable Variables
Hypothetical Constructs:
Ideas or concepts that describe a psychological
phenomenon. They are theoretical definitions!
What might be some examples?
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How do you study hypothetical constructs?
Hypothetical constructs must be operationally defined
into observable variables.
Operational Definition:
The operations or methods used to manipulate or measure
the variable(s) that relate to the hypothetical construct.
Operationally defined variables:
1. Observed and objectively measured or
controlled.
2.
Establish precisely what is meant by each
variable in the study.
3.
Can be used to develop a testable hypothesis.
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Independent Variables, Dependent Variables, and
Random Variables
Independent Variable:
A variable that is causal (or predictive).
Usually (but not always) manipulated.
“True” vs. “Participant” IV’s
Dependent Variable:
A measured or observed variable.
Influenced (or predicted) by the IV.
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Random Variables (Extraneous or irrelevant variables):
Factors other than the independent variable that can
influence the dependent variable.
Also:
Participant’s Expectations
Experimenter Bias
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2.
Select an appropriate method of researching the
problem
There are two major types of research:
1.
Descriptive/Correlational:
Focuses on carefully mapping out a situation, and
examining how two or more events change together
over time. Allows prediction!
General correlational hypothesis:
Changes in X are related to changes in Y
2.
Experimental:
Focuses on the identification of cause and effect by
manipulating one variable to examine its effect on
another variable.
General experimental hypothesis:
Changes in X cause changes in Y
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Types of Descriptive/Correlational Research
Naturalistic Observation: observes people or animals in
natural environment.
Example: observing people in a queue
Advantages:
Best way to examine a phenomenon!
Disadvantages:
Observer Bias
Lack of Control
Observer Interference
People behave differently when watched
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Types of Descriptive/Correlational Research
Case Studies: a detailed examination of a particular
behavior, mental process, disorder, etc. found in a single
individual.
Example: interviewing someone with brain damage.
Advantages:
May be the only way to study a rare or complex
phenomenon...
Disadvantages:
Difficult to draw conclusions based on only a single
case
Highly subjective
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Types of Descriptive/Correlational Research
Survey (Attitude) Research: ask self-report questions to a
large number of people. Examine relationships between
attitudes and behavior.
Example: Do attitudes about job satisfaction relate to job
performance?
Advantages:
Easy
Cheap
Fast way to obtain a lot of information!
Disadvantages:
Questions may be poorly constructed
People may lie about responses or not be able to
answer accurately
Opinions may not relate to actual events in real world
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Types of Descriptive/Correlational Research
Survey (Ability) Research: measurements of attributes,
skills, abilities, or task performance are measured with as
much precision as possible. Relations between scores are
examined.
Example: measuring SAT’s and also college GPA to
examine the relationship.
Advantages:
Allows for prediction, best option when no control
Disadvantages:
All of the disadvantages of attitude survey research
Measurement error
Lack of control
The “Third variable” problem
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Types of Experimental Research
True Experiments: manipulate an independent variable
(IV) to see how it influences a dependent (measured)
variable (DV).
Differences are compared between a group that was
randomly assigned to receive one level of the IV and one
or more groups that were randomly assigned to receive a
different level of the IV or a placebo.
Example: comparing recall between three groups or
participants, 500 mg Super Ginkgo, 250 mg Super
Ginkgo, and placebo.
Advantages:
Can establish a cause and effect relationship between
variables
Greatest amount of precision and control
Disadvantages:
May be artificial (external validity)
Practical and ethical concerns
Still can never rule out chance
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Types of Experimental/Causal Research
Quasi-Experiment: when it is neither possible nor ethical
to randomly group people by manipulation of variables.
Example: Comparing visual memory between females
and males.
Advantages:
Still enables you to (more or less) examine cause and
effect
Disadvantages:
Can't control random assignment so it's harder to
draw conclusions.
It’s really a correlational design.
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Some Examples of IV’s, DV’s, and Random Variables
Type of
IV
DV
possible
Research
RandomVar.
Causal:
Hours of
lever pressing room
True Exp.
water
for water
temperature
deprivation
Causal:
Number of
play time
prior
True Exp.
hidden
boredom
switches a toy
Causal:
Dose of
motor activity tolerance to
True Exp.
caffeine
caffeine
Causal:
Sex (F or M)* Accuracy of previous
Quasi Exp.
depth
experience
perception
with task
Relational:
SAT scores* college GPA study or test
measurement
anxiety
Relational:
IQ score*
yearly income SES
measurement
Relational:
scores on the time spent
like or
survey
(self report)
observing a
dislike for
Perceptual
novel
the subject
Curiosity
photograph
matter of the
scale*
photograph
*Not a true IV. These are “participant” IV’s. Participants
cannot be randomly assigned to levels of the IV. Some
researchers won’t even call them IV’s, but rather “predictors.”
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3.
Recruit participants, conduct study, collect data
Samples and Populations
Representativeness & Sampling bias
Random sampling vs. Random assignment
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4.
Conduct statistical analyses that will facilitate
description and interpretation of your data in
order to draw conclusions
Descriptive Statistics: summarize the data
I.
Central Tendency: a "typical" score or value
Mean: average score
(total/n)
Mode: most frequently occurring score
Median: the middle score (1/2 above and 1/2
below)
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II. Variability: how much the scores differ from one
another; the spread in a data set.
Range: the range in scores (highest - lowest)
Standard Deviation: standardized average
difference of each score from the mean
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III. Relational Statistics: indicates how two or more
variables are related to one another.
Correlation coefficient:
the direction and size of relationship between two
variables
(ranges from 1.0 to -1.0).
Regression:
tells you how well scores on one variable (X) can
predict changes in scores on another variable (Y).
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IV. Inferential Tests
What is the probability that your findings are genuine?
t-test: used to compare two group means to see if
they are "significantly*" different from one another.
ANOVA: used to compare more than two group
means.
*a "significant" result means that the difference is not
likely to be due to chance.
5.
Report your findings, and share with the scientific
community!
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ALSO BE SURE TO READ ABOUT:
1. CRITICAL THINKING
2. ETHICAL GUIDELINES FOR PSYCHOLOGISTS