The single factor ANOVA tests for mean differences between 3
or more groups by comparing
Each
population’s variance.
Each
sample’s variance.
Overall
versus average sample variance.
Overall
versus average population variance.
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The Two Factor ANOVA with Replication primarily tests for
interactions between the variables.<br>
The Two Factor ANOVA with Replication primarily tests for
interactions between the variables.
True
False
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Excel’s single factor ANOVA output includes the effect size
measure.
Excel’s single factor ANOVA output includes the effect size
measure.
True
False
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Excel’s Two Factor ANOVA without Replication <br>
Excel’s Two Factor ANOVA without Replication
provides
a method to test multiple (>2) variables at the same time.
provides
a way to remove the influence of one variable on another variable.
tests
for interaction impact among the factors being tested.
requires
a large p-value to reject all of the tested hypothesis statements.
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A single factor ANOVA output includes information on<br>
A single factor ANOVA output includes information on
Means
Variances
Significance
of outcome
All of
the above
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The alternate hypothesis for the single factor ANOVA states
that all means differ.<br>
The alternate hypothesis for the single factor ANOVA states
that all means differ.
True
False.
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Setting up data entry for the single factor ANOVA in Excel
involves<br>
Setting up data entry for the single factor ANOVA in Excel
involves
an
estimated value for the common mean.
an
estimated value for the common variation.
data
presented in a column format.
data
presented in a table format.
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The Two Factor ANOVA with Replication primarily tests for
mean differences.<br>
The Two Factor ANOVA with Replication primarily tests for
mean differences.
True
False.
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Excel’s single factor ANOVA does not have a related Effect
Size measure associated with it.
Excel’s single factor ANOVA does not have a related Effect
Size measure associated with it.
True
False
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What is the best reason to perform an ANOVA test rather than
multiple t-tests?<br>
What is the best reason to perform an ANOVA test rather than
multiple t-tests?
to
ensure the overall confidence level remains the same.
It is
easier to perform one test than several tests.
This
depends upon the individual preference of the researcher.
We shouldn’t – multiple t-tests are more precise.
