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Suppose you use a vision system to identify if an appropriate amount of adhesive has been added by a dispensing operation. The vision system categorizes each unit as accept or reject after the adhesive is added. If a part is rejected, it goes to a repair loop where it is re-tested. If there is an actual failure, it is reworked. The repair loop operator has been complaining of unnecessary extra work due to errors with the vision system. To better understand the problem, they conduct a special attribute agreement analysis of the vision system. Here, they compare results of the vision system with an expected standard. (Thus, assume the column \"Standard\" is what the vision should get and the column 'Inspect result' is what the vision system is reporting.) Hint: Use Multiple Columns setting with Attribute Agreement and enter the above 2 columns of results to compare (See Options for Cohen Kappa). May also use STAT Tables Cross Tabulation or Tally Outcome Results to identify all possible outcomes. Requirements: % Match 95% and Measure of Association 0.7 Based on your analysis, which of the following would most likely be concluded? a. % Match is 98% and Cohen Kappa Statistic = 0.91. Thus, the measurement system meets all requirements and no changes are necessary b. % Match is 46% and Cohen Kappa Statistic = 0.44. Thus, they need to redesign an entirely new vision system to significantly reduce all types of measurement error c. % Match is 78% and Cohen Kappa Statistic = 0.24. They need to focus on improving detection (vision system result indicates accept when it should be rejecting) d. % Match is 78% and Cohen Kappa Statistic = 0.24. They need to primarily focus on reducing false alarms (vision system indicates reject when it should be accepting)