Term
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Definition
| Measurement scale in which the numbers have to quantitative data, but rather serve to identify categories into which events can be placed. i.e. numbers on the backs of jerseys. |
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Term
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Definition
| Numbers assigned for relative ranking. i.e. Jenny was 1st, Mark was 2nd... etc. |
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Term
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Definition
| Measurement Scale in which numbers refer to quantities and intervals are assumed to be of equal size. (Temperature). |
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Term
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Definition
| Measurement scale in which numbers refers to quantities and intervals are equal size and a score of Zero denotes a total absence of the thing being measured. |
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Term
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Definition
| A set of statements that summarizes and organizes existing information about some phenomenon, provides an explanation, and serves as a basis for making predictions to be tested empirically. |
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Term
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Definition
χ2 (chi square) test of independence tests if verdict is independent from fault
by testing if the observed proportions are different from those expected by
chance. |
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Term
| Limitations of X^2 Test of Independence |
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Definition
•As sample size grows you almost always
find violations in independence.
•The test only tells you if the two variables
are not independent....it does not tell you
to what degree the two variables are
associated. |
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Term
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Definition
• Measure of the size of a linear relationship
between two variables.
• Ranges from a perfect negative correlation -1.00 to
a perfect positive correlation +1.00
• If r = 0 then no linear relationship exists.
• Dividing
by
the
product
of
the
standard
deviasions
of
X
and Y
makes
our
measure
of
correlation
(Pearson
r)
and
also
makes
it
independent
of
the
units
the
variables
are
measured
in. |
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Term
| Correlation and Causation |
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Definition
•X could cause Y.
•Y could cause X.
•The correlation could be spurious
•A third unseen variable is actually
responsible for the relationship.
•Some correlations can be due to just
chance or due to accidental factors not at
all linked to each other. |
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Term
| Cross-Lagged Panel Correlation |
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Definition
Measures the relationship between two variables separated by time.
•A type of correlational research design
used to deal with the directionality
problem; if variables X (violent TV) and Y
(aggression) are measured at two different
times and if X precedes Y,
•then X might cause Y
•but Y probably does not cause X. |
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Term
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Definition
| An attractive, red-headed boy, who often speaks in silly accents. Note - needs to work on listening skills and always have an abundance of chocolate on hand. |
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Term
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Definition
the degree to which an experiment is methodologically sound and compound free.
In an internally valid study, the results measured by the DV, are directly associated with the IV and are not the result of some other factor.
Threats to Internal Validity:
1) Pre-Post Studies
2) History and Maturation
3) Regression
4) Testing (actually being measured) and Instrumentation (changes in measurement technique from pre to post test).
5) Participants are Non-Equivalent in groups
6) Attrition (Participants don't finish study) |
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Term
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Definition
| mediation model is one that seeks to identify and explicate the mechanism that underlies an observed relationship between an independent variable and a dependent variable via the inclusion of a third explanatory variable, known as a mediator variable. Rather than hypothesizing a direct causal relationship between the independent variable and the dependent variable, a mediational model hypothesizes that the independent variable causes the mediator variable, which in turn causes the dependent variable. The mediator variable, then, serves to clarify the nature of the relationship between the independent and dependent variables |
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Term
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Definition
• Step 1: Estimate the association between the IV & DV (c).
• Step 2: Estimate the association between the Mediator & IV (a).
• Step 3: Estimate the association between the mediator and the
DV (b)
• Step 4: The association between the IV an DV must be reduced
when the Mediator is accounted for. |
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Term
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Definition
Most commonly, regression analysis estimates the conditional expectation of the dependent variable given the independent variables — that is, the average value of the dependent variable when the independent variables are held fixed.
If we know "Amount of Steroids Taken" can we predict "Amount Bench Pressed" |
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