Bihistogram

Full name Microsoft.VisualBasic.Data.ChartPlots.Statistics.Bihistogram Assembly Microsoft.VisualBasic.Data.ChartPlots.Statistics Members 1

Bihistogram

http://www.itl.nist.gov/div898/handbook/eda/section3/bihistog.htm

The bihistogram is an EDA tool for assessing whether a before-versus-after engineering modification has caused a change in

location;
variation; Or
distribution.

It Is a graphical alternative To the two-sample t-test. The bihistogram can be more powerful than the t-test In that all Of the distributional features (location, scale, skewness, outliers) are evident on a single plot. It Is also based on the common And well-understood histogram.

01 Syntax

Microsoft.VisualBasic.Data.ChartPlots.Statistics.Bihistogram

02 Methods

Name	Overloads	Summary
Plot	1	The bihistogram can provide answers to the following questions: + Is a (2-level) factor significant? + Does a(2 - level) factor have an effect? + Does the location change betw…

03 Members

method Plot #

Plot

The bihistogram can provide answers to the following questions:

Is a (2-level) factor significant?
Does a(2 - level) factor have an effect?
Does the location change between the 2 subgroups?
Does the variation change between the 2 subgroups?
Does the distributional shape change between subgroups?
Are there any outliers?

The bihistogram is an important EDA tool for determining if a factor "has an effect". Since the bihistogram provides insight into the validity of three (location, variation, and distribution) out of the four (missing only randomness) underlying assumptions in a measurement process, it is an especially valuable tool. Because of the dual (above/below) nature of the plot, the bihistogram is restricted to assessing factors that have only two levels. However, this is very common in the before-versus-after character of many scientific and engineering experiments.