VarTable

Summary table from dt, used for vignette

datasets

An implementation of the Partition Of variation (POV) method as
developed by Dr. Thomas A Little <https://thomasalittleconsulting.com> in
1993 for the analysis of semiconductor data for hard drive manufacturing.
POV is based on sequential sum of squares and is an exact method that
explains all observed variation. It quantitates both the between and within
factor variation effects and can quantitate the influence of both continuous
and categorical factors.

Paul Deen

Partition of Variation Variance Component Analysis Method

VarTable function

A data frame with 9 rows and 5 variables:<dl class="dl-horizontal">
 <dt>Machine</dt><dd>3 Levels of different machines used for production</dd>
 <dt>Metrology</dt><dd>3 Levels of different metrology used for measurement</dd>
 <dt>rowVariance</dt><dd>Sample variance of the respone</dd>
 <dt>rowN</dt><dd>Sample size of the response at each factor combination</dd>
 <dt>popVar</dt><dd>Sample variance rescaled to population variance by multypling by (N-1)/N</dd>
</dl>

Format

Summary table from dt, used for vignette — VarTable

A data frame with 9 rows and 5 variables:<dl class='dl-horizontal'>
 <dt>Machine</dt><dd>3 Levels of different machines used for production</dd>
 <dt>Metrology</dt><dd>3 Levels of different metrology used for measurement</dd>
 <dt>rowVariance</dt><dd>Sample variance of the respone</dd>
 <dt>rowN</dt><dd>Sample size of the response at each factor combination</dd>
 <dt>popVar</dt><dd>Sample variance rescaled to population variance by multypling by (N-1)/N</dd>
</dl>

VarTable: Summary table from dt, used for vignette

Description

Usage

Arguments

Format