# 20 - remains in control To evaluate the control of a...

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The statistical description of stability over time requires that the pattern of variation remain stable, not that there be no variation in the variable measured. Statistical control: A variable that continues to be described by the same distribution when observed over time is said to be in statistical control, or simply in control. Control charts are statistical tools that monitor a process and alert us when the process has been disturbed so that it is now out of control. This is a signal to find and correct the cause of the disturbance. Exploratory data analysis: Use of graphs and numerical summaries to describe the variables in a data set and the relations among them. Process-monitoring conditions: Measure a quantitative variable x that has a Normal distribution. The process has been operating in control for a long period, so that we know the process mean μ and the process standard deviation σ that describe the distribution of x as long as the process
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Unformatted text preview: remains in control. To evaluate the control of a process with given standards μ and σ, make an x-bar control chart (or x-bar chart) as follows: *Plot the means x-bar of regular samples of size n against time. *Draw a horizontal center line at μ. *Draw horizontal control limits at μ ± 3σ / √(n). Any x-bar that does not fall between the control limits is evidence that the process is out of control. The purpose of a control chart is not to ensure good quality by inspecting most of the items produced. Control charts focus on the process itself rather than on the individual products. All processes have variation. There are two signals indicating that a process is out-of-control. The first is obtaining a sample mean that is below or above .The second signal is having nine sample means in a row either above the center line or below the center line....
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