Steps in the Research Process:
Designing the Study
Research Variables



Independent variables are the conditions
manipulated by the experimenter.
Dependent variables are measured as the
results of the experiment (what the participants
are doing differently after receiving the
experimental manipulation
manipulation))
Confounding variables are extraneous factors
present in an experiment that may affect the
results.
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Conducting an Experiment




Other Research Variables
Select research participants that represent the
population of interest and randomly divide them
into groups.
Manipulate the independent variable.
Measure changes
g in the dependent
p
variable.
Control for extraneous variables that might
confound the results of the experiment.
experiment.

Individual difference variables related to
the participants (quasi(quasi-independent
variables).
• These are often minimized or controlled such
that the experimental results are more clearly
seen.
• Examples: Age, gender, diagnosis, intelligence,
grade level, income level, living arrangement,
sexual orientation, etc.
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Measuring the Dependent Variable

Measurement Scales
Participant responses are often measured
as dependent variables.

Nominal (non(non-ordered categories)
• Physiological responses (heart rate, sweating,
body temperature, etc.)
Self--Reports
p
((ratings
g on scale,, descriptions
p
of
• Self
emotions, descriptions of past or future
behaviors, etc.)
• Behavior measures (direct observations of
behaviors like hand movements, pushups,
hugs, etc.

• No numerical properties, only named categories
Example: How do you feel today? (Circle one) happy
sad
anxious
excited

Ordinal (ordered categories)

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• Could have numerical properties but only for ordering
the categories from first to last
Examples: Academic grades, places in a race, ranking
schools or sports teams
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Measurement Scales

Validity of Scales
Interval

• Has numerical properties with equal distance
between each number on the scale but no zero
point (representing a total absence of the thing
being measured).
• Example: Rating beauty on a scale of 11-10

Ratio
• Same as the interval scale (equal intervals
between numbers) except there is a zero
point.
• Examples: time measures, response rate
measures, other physical measurements.
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Construct validity:
validity: scale measures the behavior it was
designed to measure.
• A measure with high construct validity will provide an
accurate measure of the behavior of interest.
• For example,
p children who are 5 yyears old will not
understand the items on an anxiety questionnaire
standardized on adults. If this questionnaire was used
as the dependent variable measure with young
children, the responses would likely be inaccurate
and lower the construct validity of the study.
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Validity of Scales

Face validity
validity:: intuitively, scale appears to have high
validity.
• This means that, on the surface, the scale seems to
measure what you think it does.


If you want to know how well someone performs a task under
different conditions, an accuracy scale seems to be an
intuitively good measure for this behavior
behavior..
If you want to know about someone’s mood, asking about
their mood seems as if it will measure what you want to
measure.
• If items on a questionnaire seem to relate to the
concept being measured, then the questionnaire has
good face validity.
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