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Statistical Reference Guide
Compare groups
Testing equality of means/medians (independent samples)
Test if there is a difference between the means/medians of two or more independent samples.
Select a cell in the dataset.
On the
Analyse-it
ribbon tab,
in the
Statistical Analyses
group,
click
Compare Groups
, and then click the hypothesis test.
The analysis task pane opens.
In the
Y
drop-down list, select the quantitative response variable.
In the
X
drop-down list, select the categorical factor variable identifying the groups.
If performing a 2 sample hypothesis test:
In the
Hypotheses
drop-down list, select the null and directional alternative hypotheses.
In the
Hypothesized difference
edit box, type the expected difference under the null hypothesis.
If performing a k sample hypothesis test:
In the
Hypothesis
drop-down list, select the null and alternative hypotheses.
Optional:
To compare the p-value against a predefined significance level, in the
Significance level
edit box, type the maximum probability of rejecting the null hypothesis when in fact it is true (typically 5% or 1%).
Click
Calculate
.
Related concepts
Equality of means/medians hypothesis test
Related reference
Dataset layout
Tests for means/medians
Available in Analyse-it Editions
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Method Validation edition
Quality Control & Improvement edition
Ultimate edition
What is Analyse-it?
Administrator's Guide
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Statistical Reference Guide
Distribution
Compare groups
Calculating univariate descriptive statistics, by group
Side-by-side univariate plots
Creating side-by-side univariate plots
Equality of means/medians hypothesis test
Equivalence of means hypothesis test
Tests for means/medians
Testing equality of means/medians
Testing equivalence of means
Difference between means/medians effect size
Estimators for the difference in means/medians
Estimating the difference between means/medians
Multiple comparisons
Mean-Mean scatter plot
Multiple comparison procedures
Comparing multiple means/medians
Homogeneity of variance hypothesis test
Tests for homogeneity of variance
Testing homogeneity of variance
Study design
Compare pairs
Contingency tables
Correlation and association
Principal component analysis (PCA)
Factor analysis (FA)
Item reliability
Fit model
Method comparison
Measurement systems analysis (MSA)
Reference interval
Diagnostic performance
Control charts
Process capability
Pareto analysis
Study Designs
Bibliography
Version 5.40
Published 29-Jul-2019
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