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Statistical Procedure Control

 Statistical Method Control Article

1 . The Wall Street Journal content (Sept. 24 2012) paperwork how " American Flight companies continued to rack up excessive numbers of airline flight delays and cancellations, blaming a dispute with its fliers union. The union, meanwhile, denied that pilots disrupted flights thoroughly. " " By my own calculations, " writes a Dallas Early morning News (Sept. 20, 2012) reporter, " the number of pilots on ill leave was 11 fliers higher on Sept. 18, 2012, than on September. 18, 2011(1). That feels like an increase in sick and tired leave usage". (See the line chart chart below utilized to make this point).

Can your same set of data be applied to make opposite points within an argument? It can not that statistics lie, it is even more in the way you present each of the available data points, as can see through this example about the alleged " sick out" of American Air carriers pilots. This is a 13 month " snapshot" of percent of aviators out sick at American Airlines:

Date% Sick

9/18/20115. 0%

10/18/20119. 5%

11/18/20115. 0%

12/18/20116. 4%

1/18/20125. 4%

2/18/20126. 6%

3/18/20126. 6%

4/18/20125. 9%

5/18/20127. 1%

6/18/20127. 3%

7/18/20126. 1%

8/18/20126. 6%

9/18/20127. 6%

Counters the union: " Contrary to says by managing, we have proved that preliminary sick costs have not deviated from famous norms".

a)Do you agree with the union if the lower-control limit (LCL) is 2 . 94%, as well as the upper-control limit (UCL) can be 10. 15% given the 3-sigma p-chart showing the percent of pilots sick and tired? (Hint: Observe note (1) for the sample size). Do not forget to plot the middle line. b)What happens when you use 2-sigma control limits? Recalculate the control limits and discuss just how your interpretation changes and why? c)Alternatively, what happens should you exclude the first two months? Recalculate the control limitations and discuss whether the interpretation improvements. If so , how?

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