Normal Variation Flashcards

1
Q

What is normal variation?

A

All processes experience normal random variation. This is often modeled with a bell-shaped curve and can be described with statistical data parameters including the mean, median, range and standard deviation.

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2
Q

When do you use SPC analysis?

A

You will need to determine the pattern of variation. Once the variation has become normal variation, you can begin to control the process.

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3
Q

How is normal variation represented?

A

In a bell shaped curve which is a symmetrical distribution that has a high center peak and with upper and lower edges that approach zero.

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4
Q

What is another name for a bell shaped curve?

A

Gaussian distribution

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5
Q

Who is the Gaussian distribution named after?

A

Carl Gauss the father of the science of statistics

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6
Q

What is the MEAN

A

this is the average value of all the items in a data set. Meaning you add all the values together and then divide by the number of items in the data set. The result is your mean.

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7
Q

What is range?

A

This is the span from the smallest value to the largest value in the data set.

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8
Q

Standard Deviation

A

This is a statistical measure of the typical spread of the data. It starts with the difference of each value from the mean value, which is called a deviation. It then squares those deviations, determines the average of those and then takes the square root of that number.

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9
Q

What can a standard deviation be used to predict?

A

The standard deviation for a normal curve can be used to predict the percentage of values in the data set that will fall within a span

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10
Q

What is 3+- standard deviations

A

in SPC is the span from minus 3 standard deviation to plus 3 standard deviations. This span will contain 99.73% of all the data values in the data set. This range was used by Walter Shewhart when first developing SPC control charts.

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11
Q

What does a normal distribution tell you?

A

When your data set for a process parameter is represented by a normal distribution, you know you are dealing with random variation. This type of process is an ideal candidate for statistical process control.

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