Gag Order Agreement

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					                                Instructions




Attribute (Discrete) Gage R & R Effectivenes
Instructions:
  1)   The following spreadsheet is used to calculate an Attribute GR&R Effectiveness, in wh
       100 samples can be evaluated, using 2 or 3 operators.
  2)   In the Data Entry worksheet fill in the appropriate information in the Scoring Report se
       enter the type of Attributes you are evaluating in the Attribute Legend section. YOU M
       THE INFORMATION IN THE ATTRIBUTE LEGEND SECTION OR THE SPREADSHE
       WILL NOT WORK. First attribute MUST be the "good" result and second attribut
        MUST be the "bad" result. The attributes can be either alpha or numeric, e.g. Yes,
        go, stop; or 1, 2. You must be consistent throughout the form and spell properly
       will work as the spreadsheet compares what is in each cell.
  3)   If you or an expert has selected samples to be evaluated and you know what attribute
       samples are, enter this information in the Attribute sample column. This will enable y
       how well each operator can evaluate a set of samples against a known standard. You
       need to enter information in this column for the spreadsheet to work.
  4)   You do not have to specify how many operators or the # of samples that you will be ev
       during the test. Simply enter the data into the spreadsheet under the specific operato
       the attributes must be spelled properly or the spreadsheet will not analyze the d



       Details from included example - numbers obtained from data entry and statistical repo
    Sample Size        14   < Try out different combinations of number of samples and number
      # Matches        11   < to see the effects of sample size. In this case, a sample size of
       95% UCL     95.3%    < one non-match will yield a 17% confidence interval. In order to g
Calculated Score   78.6%    < reliability in estimates of efficiency, large sample sizes will be req
        95% LCL    49.2%




                                  Page 1
                                                    Instructions




R Effectiveness

ute GR&R Effectiveness, in which up to

mation in the Scoring Report section and
ribute Legend section. YOU MUST ENTER
ECTION OR THE SPREADSHEET
 d" result and second attribute
 er alpha or numeric, e.g. Yes, No; pass, fail;
 t the form and spell properly, anything

 d and you know what attributes these
 ple column. This will enable you to determine
 gainst a known standard. You do not
eadsheet to work.
# of samples that you will be evaluating
 eet under the specific operator. Remember
dsheet will not analyze the data correctly.



 data entry and statistical report worksheets: Breakdown for Operator 2
umber of samples and number of matches
In this case, a sample size of 30 with
nfidence interval. In order to get reasonable
, large sample sizes will be required.




                                                      Page 2
Data Entry




 Page 3
               Statistical Report - Attribute Gage R&R Study
                                  DATE:
                                 NAME:
                              PRODUCT:
                              BUSINESS:

                                   % Appraiser                %Score vs Attribute
Source                Operator#1 Operator#2 Operator#3 Operator#1 Operator#2 Operator#3
Total Inspected           14             14      14       14          14          14
# Matched                 14             11      14       11           9          10
Type I Error (Test "Bad", when actually "Good")                  1            1       3
Type II Error (Test "Good", when actually "Bad")                 2            1       1
Mixed (Test mixed "Good" and "Bad")                              0            3       0
95% UCL                   100.0%          95.3%  100.0%    95.3%       87.2%      91.6%
Calculated Score          100.0%          78.6%  100.0%    78.6%       64.3%      71.4%
95% LCL                    76.8%          49.2%   76.8%    49.2%       35.1%      41.9%


                       Screen % Effective Score      Screen % Effective Score vs Attribute
Total Inspected                  14                                    14
# in Agreement                    8                                     6
95% UCL                           82.3%                                 71.1%
Calculated Score                  57.1%                                 42.9%
95% LCL                           28.9%                                 17.7%
                                       Calculations




Known Population                 Operator #1                         Operator #2             O
Sample #   Attribute   Try #1   Try #2  within    known   Try #1   Try #2   within   known
    1          1         1        1        1        1       1        1         1       1
    2          1         1        1        1        1       1        1         1       1
    3          2         2        2        1        1       2        1         0       0
    4          2         2        2        1        1       2        2         1       1
    5          2         2        2        1        1       1        2         0       0
    6          1         1        1        1        1       1        1         1       1
    7          1         2        2        1        0       2        2         1       0
    8          1         1        1        1        1       1        1         1       1
    9          2         1        1        1        0       1        1         1       0
   10          2         1        1        1        0       2        2         1       1
   11          1         1        1        1        1       1        1         1       1
   12          1         1        1        1        1       1        1         1       1
   13          2         2        2        1        1       2        2         1       1
   14          2         2        2        1        1       1        2         0       0
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     Calculations


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                              Calculations


    95
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   100
% Appraiser Score   100.00%              78.57%   78.57%   64.29%




                                Page 7
                                          Calculations




          Operator #3              Y/N       Y/N
Try #1   Try #2  within   known   Agree     Agree
  2        2        1       0     FALSE     FALSE
  2        2        1       0     FALSE     FALSE
  2        2        1       1     FALSE     FALSE
  2        2        1       1     TRUE      TRUE
  2        2        1       1     FALSE     FALSE
  1        1        1       1     TRUE      TRUE
  2        2        1       0     TRUE      FALSE
  1        1        1       1     TRUE      TRUE
  1        1        1       0     TRUE      FALSE
  2        2        1       1     FALSE     FALSE
  1        1        1       1     TRUE      TRUE
  1        1        1       1     TRUE      TRUE
  2        2        1       1     TRUE      TRUE
  2        2        1       1     FALSE     FALSE




                                            Page 8
Calculations




  Page 9
                   Calculations




100.00%   71.43%




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