This PRM Logistic Regression quiz assesses understanding of logistic regression versus other statistical methods, focusing on its unique assumptions and metrics. It evaluates how logistic regression handles categorical dependent variables and the significance of findings in research contexts.
Categorical, continuous
Continuous, categorical
Dichotomous, categorical
Interval, continuous
None of the above
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1,2,3
2,3,4
3,4,5,
Is flexible with all 5
Is strict with all 5
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In MANOVA, the dv has to be categorical but an underlying continuous distribution
In DFA, the dv has to be categorical but an underlying continuous distribution
In LR, the dv has to be categorical but an underlying continuous distribution
Standard, statistical & heirarchical regression are all variable selection methods of LR.
C and d
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R squared, ss, -2LL
Ss, ss squared, -2LL
Ss, r squared, -2LL
-2LL, ss, r squared
-2LL, ss squared, r squared
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True
False
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MANOVA
ANOVA
DFA
LR
MR
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1
Higher than 1
Lower than 1
Close to 1
A fraction of 1
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Below 1, less likely
Below 1, more likely
Close to 1, less likely
Close to 1, more likely
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Marketing
Environmental research
Health research
Tourism
Hospitality
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Proportion of variation in the response variable explained by the specific model
Proportion of variation in the explanatory variable explained by the specific model
It is used as a measure of effect size
B and c
None of the above
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Close to 1
Of 1
Higher than 1
Less than 1
None of the above
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You are less likely to have a high information score if you are male.
You are less likely to have a high information score if you are female.
You are equally likely either way.
The highest reading before 1.
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True
False
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MANOVA
ANOVA
DFA
LR
MR
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ANOVA
MANOVA
DFA
LR
MR
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Continuous
Dichotomous
A and b
Categorical
Whatever you like
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False
True
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False
True
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The observed data times what you can model plus eror
Quite simply, the observed data is the result of what you can model plus error
Error plus any data and model varianace
Is an interplay between variance and error variance
None of the above
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Structured, involved, relative.
Experimental, looking for an effect, trying to prove relationships.
Experimental, looking for an effect, not looking for an effect.
Non-experimental, causal, not looking for an effect.
Non-experimental, looking for an effect, trying to prove relationships.
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All, some, few.
All, minimum, subset.
All, some, subset.
All, best, subset.
They all use the same number of IV's.
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True
False
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3,2,1
1,2,3
2,1,3
3,1,2
1,3,2
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Semi-partial correlation, are not
Partial correlation, are not
Semi-partial correlation, are
Partial-correlation, are
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