2-4 Flashcards
causal vs correlational relationships
Causal association
• One variable directly or indirectly causes changes in another
• Unidirectional
• Bidirectional
Correlational relationship
• Changes in one variable accompany (covary with) changes
in another
• CORRELATION IS NOT CAUSATION
how do we determine whether one variable caused the other?
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What is the main purpose of correlational research/designs?
- When gathering data in the early stages of research
- When manipulating an IV is impossible or unethical
- When you are examining two or more naturally occurring variables
What are the limitations of correlational research?
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directional problem
Not always possible to specify the direction in which a causal arrow points`
Not always possible to specify the direction in which a causal arrow points
directional problem
Why can’t we infer causation from correlational relationships among variables?
third-variable problem and directional problem
experimental research
an iv is manipulated and a dv is measured
strengths of experimental research
Identification of causal relationships among
variables
limitations of experimental research
sometimes can’t manipulate variables
requires tight control
difference between IV and DV
IV: the variables that are manipulated
DV: the variables that are measured
What is internal validity?
the degree to which your design tests what it was intended to test
How is internal validity threatened?
CONFOUNDING and EXTRANEOUS VARIABLES
confounding varaibles
a variable that influences both the dependent variable and independent variable, causing a spurious association.
a variable that influences both the dependent variable and independent variable, causing a spurious association.
confounding variables
extraneous variables
any variables that you are not intentionally studying in your experiment or test.
any variables that you are not intentionally studying in your experiment or test.
extraneous variales
What are the threats to internal validity?
history maturation instrumentatoin statistical regression biased subject selection experimental mortality
history
events may occur between multiple observatoins
events may occur between multiple observatoins
history
maturatoin
participants may become older or fatigued
participants may become older or fatigued
maturation
testing
taking a pretest can affect results of a later test
taking a pretest can affect results of a later test
testing
instrumentatoin
changes in instrument calibration or observers may chance results
changes in instrument calibration or observers may chance results
instrumentation
statistical regression
subjects may be selected based on extreme scores
subjects may be selected based on extreme scores
statistical regression
biased subject selection
subjects may be chosen in a biased fashion
subjects may be chosen in a biased fashion
biased subject selectoin
experimental mortality
differential loss of subjects from groups in a study may occur
differential loss of subjects from groups in a study may occur
experimental mortality
how do we correct the problems introduced by extraneous factors?
control
random assignment
Pros and cons of laboratory settings
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pros and cons of field settings
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