Problem 7 Flashcards

1
Q

causal relationship

A

changes in the value of one variable directly or indirectly causes changes in the value of the second

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2
Q

correlational relationship

A

two variables simply change values together and may or may not influence one another, measures only linear association, bidirectional/unidirectional

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3
Q

correlational research

A

determine whether two (or more) variables covary and, if so, to establish the directions, magnitudes, and forms of the observed relationships; non-experimental research

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4
Q

third-variable problem

A

possibility that a third, unmeasured variable influences both observed variables in such a way as to produce the correlation between them

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5
Q

directionality problem

A

if two variables are causally related, correlational designs cannot determine in which direction the causal arrow points

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6
Q

predictor variable

A

used to make predictions

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7
Q

experimental research

A

strong control over variables, allow you to establish whether variables are causally related

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8
Q

experimental groups

A

receives the experimental treatment

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9
Q

control group

A

is treated identically except that it does not receive the treatment

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10
Q

demonstration

A

type of non-experimental design, resembles an experiment, lacks manipulation of an independent variable; useful for showing what sorts of behaviors occur under specific conditions, but cannot identify relationships among variables

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11
Q

confounding variable

A

varies along with your independent variable

  • -> damages internal validity
  • -> not able to establish causal relationship between independent & dependent variable
  • -> experimenter bias; avoid with blind technique
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12
Q

quasi-independent variable

A

correlational variable that resembles an independent variable in an experiment

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13
Q

cross-sectional design

A

select several participants from each of a number of age groups

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14
Q

generation effect

A

influence of generational differences in experience, which become confounded with the effects of age per se –> is confounding = threat to internal validity

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15
Q

longitudinal design

A

single group of participants is followed over some time period

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16
Q

cross-generational effects

A

conclusion drawn from the longitudinal study of a particular generation may not apply to another generation

17
Q

subject mortality

A

loss of subjects from the research over time

–> threats to external validity

18
Q

multiple-observation effect

A

multiple observations of same participants over time

19
Q

cohort-sequential design

A

combines the two developmental designs and lets you evaluate the degree of contribution made by factors such as generation effects

20
Q

Simpson’s paradox

A

association or comparison that holds for all of several groups can reverse direction when the data are combined to form a single group

21
Q

aggregating data

A

we ignore variable which then become lurking variables

22
Q

confounding

A

two variables’ effects on response variable can’t be distinguished from each other; confound variable: explanatory/independent variable, lurking variable, both

23
Q

conceptual confound

A

overlapping measurements of cause & consequence (variable)

24
Q

extraneous variable

A

all variables other than the specific variables that are studied, only becomes confound if it systematically varies with the two variables that are studied

25
common-response
changes in response and explanatory variable are caused by changes in lurking variables; lurking variable Z explains association
26
mediator variable
A --> D --> C
27
moderator variable
relationship between A and B differs according to the values of E; variable moderates the relationship between two other variables, acting like a gate
28
placebo control group
condition in which participants receive a placebo instead of the actual treatment
29
manipulation check
additional measure to assess how the participants perceived & interpreted the manipulation and/or to assess the direct effect of the manipulation
30
quasi experiment
tries to establish a causal relation between one variable and another; does not directly manipulate a variable but tries to isolate a causal influence by selection rather than manipulation
31
covariation
two variables are associated
32
precedence
the causal variable precedes the effect variable
33
matching
divide variable with much influence equally over groups
34
blocking
limited population = keep suspected confounder constant (only test women)
35
criterion variable
value is being predicted