whiskersPlot: Function to create Whiskers Charts

In qualityTools: Statistical Methods for Quality Science

Description

In a Whiskers Chart, the high and low data values and the average (median) by
part-by-operator are plotted to provide insight into the consistency between operators,
to indicate outliers and to discover part-operator interactions. The Whiskers Chart
reminds of boxplots for every part and every operator.

Usage

whiskersPlot(x, main, xlab, ylab, col, ylim, legend=TRUE, ...)

Arguments

x	needs to be an object of class gageRR.
main	a main title for the plot
xlab	a label for the x axis
ylab	a label for the y axis
col	plotting color
ylim	the y limits of the plot
legend	a logical value specifying whether a legend is plotted automatically. By default legend is set to ‘TRUE’. If the argument legend is set to ‘FALSE’ an individual legend can be added by using the function legend afterwards.
...	arguments to be passed to methods, such as graphical parameters (see par).

Details

Graphical parameters such as col or pch can be given as single characters or as
vectors containing characters or number for the parameters of the individual operators.

Note

Please do read the vignette for the package qualityTools at http://www.r-qualitytools.org.

Author(s)

Thomas Roth: [e-mail]
Etienne Stockhausen: [e-mail]

References

The idea of the plot and the example given by example(whiskersPlot) are out of:

• CHRYSLER Group LLC; FORD Motor Company; GENERAL MOTORS Corporation: Measurement System Analysis (MSA),
  p.111, 4rd ed. Southfield: AIAG, 2010.
  

See Also

gageRR
par
http://www.r-qualitytools.org

Examples

# create gageRR-object
gdo = gageRRDesign(Operators = 3, Parts = 10, Measurements = 3, 
                   randomize = FALSE)
# vector of responses                    
y = c(0.29,0.08, 0.04,-0.56,-0.47,-1.38,1.34,1.19,0.88,0.47,0.01,0.14,-0.80,       
      -0.56,-1.46, 0.02,-0.20,-0.29,0.59,0.47,0.02,-0.31,-0.63,-0.46,2.26,
      1.80,1.77,-1.36,-1.68,-1.49,0.41,0.25,-0.11,-0.68,-1.22,-1.13,1.17,0.94,
      1.09,0.50,1.03,0.20,-0.92,-1.20,-1.07,-0.11, 0.22,-0.67,0.75,0.55,0.01,
      -0.20, 0.08,-0.56,1.99,2.12,1.45,-1.25,-1.62,-1.77,0.64,0.07,-0.15,-0.58,
      -0.68,-0.96,1.27,1.34,0.67,0.64,0.20,0.11,-0.84,-1.28,-1.45,-0.21,0.06,
      -0.49,0.66,0.83,0.21,-0.17,-0.34,-0.49,2.01,2.19,1.87,-1.31,-1.50,-2.16)
 # appropriate responses      
response(gdo)=y  
# perform and gageRR                                                                 
gdo=gageRR(gdo)    
                                                                
whiskersPlot(gdo)                                                            

Example output

Loading required package: Rsolnp
Loading required package: MASS

Attaching package: 'qualityTools'

The following object is masked from 'package:stats':

    sigma


AnOVa Table -  crossed Design
              Df Sum Sq Mean Sq F value   Pr(>F)    
Operator       2   3.17   1.584  34.440 1.09e-10 ***
Part           9  88.36   9.818 213.517  < 2e-16 ***
Operator:Part 18   0.36   0.020   0.434    0.974    
Residuals     60   2.76   0.046                     
---
Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1

----------
AnOVa Table Without Interaction -  crossed Design
            Df Sum Sq Mean Sq F value   Pr(>F)    
Operator     2   3.17   1.584   39.62 1.34e-12 ***
Part         9  88.36   9.818  245.61  < 2e-16 ***
Residuals   78   3.12   0.040                     
---
Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1

----------

Gage R&R
                 VarComp VarCompContrib Stdev StudyVar StudyVarContrib
totalRR           0.0914         0.0776 0.302     1.81           0.279
 repeatability    0.0400         0.0339 0.200     1.20           0.184
 reproducibility  0.0515         0.0437 0.227     1.36           0.209
   Operator       0.0515         0.0437 0.227     1.36           0.209
   Operator:Part  0.0000         0.0000 0.000     0.00           0.000
Part to Part      1.0864         0.9224 1.042     6.25           0.960
totalVar          1.1779         1.0000 1.085     6.51           1.000

---
 * Contrib equals Contribution in %
 **Number of Distinct Categories (truncated signal-to-noise-ratio) = 4 

NULL

qualityTools documentation built on May 2, 2019, 10:21 a.m.