Normal Variation Flashcards
What is normal variation?
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.
When do you use SPC analysis?
You will need to determine the pattern of variation. Once the variation has become normal variation, you can begin to control the process.
How is normal variation represented?
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.
What is another name for a bell shaped curve?
Gaussian distribution
Who is the Gaussian distribution named after?
Carl Gauss the father of the science of statistics
What is the MEAN
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.
What is range?
This is the span from the smallest value to the largest value in the data set.
Standard Deviation
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.
What can a standard deviation be used to predict?
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
What is 3+- standard deviations
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.
What does a normal distribution tell you?
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.