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Unformatted text preview: Page 1 of 22 1 You can buy this $70 book for yourself if you find you need it. Rev. March 25, 2009 (3:46pm) E:\SWT\HA4315\Class notes\Spring 2009 version\C_18 Spg 09.wpd Reduce, reuse, restore, recycle Class Eighteen Agenda & Objectives HA 4315 I. Class activities & objectives A. Statistical Thinking and the Use of Data B. Data and Sampling. C. Memory Jogger II , Data Points, pp. 52-55. II. Instructor’s introductory BS At this point we have completed the “word” tools and are going to start the numerical tools. The Coaches Guide 1 to the Memory Jogger II provides the table below to assist in determining which tool to use with the various types of data. When you look at the list of word tools you will see that we have completed all of them we are going to do. What may have seemed like an intimidating list to you when we started should now not look so bad. Page 2 of 22 Rev. March 25, 2009 (3:46pm) E:\SWT\HA4315\Class notes\Spring 2009 version\C_18 Spg 09.wpd Reduce, reuse, restore, recycle We turn now to the tools that involve data coming from numbers. One of the major themes to keep in mind throughout the remainder of the semester is the statement by Deming: the essence of his message about quality improvement is to reduce variation. Presupposed in the idea that improvement means reduction of variation is that you know what the standard for performance should be. If you do not, then how can you know how much variation should be expected? At the same time our goal is to reduce variation, we shall also learn that part of our goal is to recognize when it is futile to seek further reduction of variation. III. Statistical Thinking and the Use of Data. A. Introductory ideas • Statistics can provide a unified language to break down barriers created by varied perceptions of how a process works. For example, someone might say “there is too much variation in the amount of time it takes to prepare a simulation for a thyroid cancer patient compared to how we were doing it before.” “Too much” is not very helpful. If we knew the average time, the range between the maximum and minimum, and the standard deviation of the variation around the average, we could make very precise statements about how the process is working now, in comparison to how it was working before. • All data collection must have a specific agreed upon objective and measurement process in order to prevent excessive variation. Following up on the example above, we could set as a goal of data collection “determining the average and variation in development of simulations for thyroid cancer radiation treatments.” We could define the measurement process as starting the timing of the event from when the prescription was received to when the completed simulation was logged in....
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This note was uploaded on 03/30/2011 for the course HA 4315 taught by Professor N/a during the Spring '11 term at Texas State.
- Spring '11