Overview of Research Designs
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Basic Research
Simply satisfies researcher's curiosity

Applied research
applies the knowledge to somehow benefit humankind

Field Research
 Takes place in more natural settings
 Less control over variables

Laboratory Research
 Takes place in laboratory
 More control over Variables

Crosssectional Research
Studies individuals of different ages at one point in time

Longitudinal Research
studies a single age group over a number of years

Quantitative Methods
Differences in amount

Qualitative Methods
Differences in kind

Descriptive Methods
 Observing and Describing behavior
 Who, what, where, when questions
 Naturalistic observation
 Surveys
 Case studies
 Correlational studies

Experimental method
Observation of causal relationships

Independent Variable (IV)
variable that is manipulated or varied by a researcher to see if it has an effect on another variable

Dependent Variable (DV)
variable that is measured to see if it is influenced by IV

Extraneous Variables
variables that affect the DV but were not manipulated by researcher

Control Variable
variable that may have an effect on the DV (over the IV) and therefore needs to be controlled for via research design or statistics

Confounding Variable
variable that may have an effect on the DV and is systematically related to IV > offers alternative explanation for the outcome of study

Type I Error (α)
False positive: we think there is a difference but in fact there is not

Type II Error (β)
False Negative: we think there is no difference but in fact there is a difference

Power
 reject false null hypothesis
 True Positive: we think there is a difference and there really is one

Effect Size
 Measure of the strength of the relationship between/among variables
 Determines if differences are not only statistically significant, but also whether they are iportant

Ways to Increase Power
 Be careful how you measure your variables
 Use more powerful statistical analyses
 Use designs that provide good control over extraneous variables
 Restrict your sample to a specific group of individuals
 Increase your sample size > reduces error variance
 Maximize treatment manipulation