Aabel 3 More Other Information

How to stepwise X-zooming into a region of data?

X-zooming feature is designed for walking through a hierarchy of numeric or categorical data. It excludes the data that are outside the zoomed area of the graph.

When you use this feature, the exclusion of the data is not a visual effect. These data are excluded from the Visualization and Statistics Pipeline, and hence are excluded from any further analysis (e.g. they will not be included in regression calculations).

X-zooming can be applied to all graphs of exploratory nature, to a large number of plots displaying data points, to column and bar graphs, to histograms, and to graphs, using categorical data such as mosaic, spine plots, Pareto or other categorical histograms, to sequence alignment diagrams, to stereographic scatter plots, etc. tc.

X-zooming can be performed:

• Using the X-zoom tool and dragging around the region of data of interest
• Selecting the region of data of interest and using the contextual menu command

What worksheet layouts are supported by Aabel 3 when use One-Way ANOVA feature?

One-way ANOVA is also known as single-factor between-subjects ANOVA, completely randomized single-factor ANOVA. The computed test statistic evaluates if there is a significant difference between at least two of the group means in a set of k means.

For this ANOVA design, Aabel supports two different worksheet layouts.

• The layout I allows storing the design experimental scores (response data) from all of the k >= 3 samples/groups in a single numeric column, and uses the levels of the design single factor (A) to split the data accordingly.
• The layout II requires storing the design experimental scores (response data) from each sample/group in a separate numeric column, i.e., each column represents one of the levels of the design (between-subjects) single factor.

What are includes by Multiple Comparisons Accompanying Analysis of Covariance (ANCOVA) ?

The multiple comparisons/post-hoc tests accompanying the analysis of covariance are conducted on The Adjusted Group/Treatment Means, and include:

• Tukey's HSD test
• Scheffé test
• The expressions employed to compute the test statistic for the tests accompanying ANCOVA are different from those used for tests accompanying ANOVA. The screenshot below is an example for the Tukey's HSD test accompanying ANCOVA, where computing adjusted group/treatment means determines what the scores on dependent variable would be if the groups did not differ on the covariate.

Why is outlier detection import in the outlier analysis?

Outlier detection is import for two reasons:

• Outliers can provide valuable information on data quality or highlight atypical patterns.
• Outliers tend to pull the mean vector towards themselves and inflate the variance in their direction, and can hence influence the result of tests that are based on comparing means or include variances in computational procedures.