Minitab: Understanding Normality and What Chart To Use.

B

Brad Gover - 2010

#1
:bigwave:Hi all, it is me again. I have a question on determining if a set of data is normal at a CI = 95%. Can I use Minitab's probability plot (not probability distribution plot) under the "Graph" tab. With a CI = 95% my p-value for one set of data is 0.035 which to my understanding is not normally distributed. Another data set the p-value is 0.625 which would be above the alpha level and thus normally distributed. Is this the approperate chart to use? If so, are my conclusions correct?

With regards to the normality test under the "stat->basic stat->normality test. When I do this on the first data set above, I get the same p-value = 0.035. Are both the same? If not what is the difference and which one is normally used for checking normallity?
Questions, Questions, lots of Questions...But having so much fun too!:biglaugh:
 
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Miner

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#2
Minitab often has multiple ways of performing the same test. The two that you describe are both performing the same base test, but each has slightly different secondary outputs. One focuses more on the graphical aspects than the other.

Your interpretation of the p-values is essentially correct.

To be precise, 0.035 means that there is a 3.5% chance that the data came from a normal distribution. This is a low probability, so we reject the hypothesis that the data are from a normal distribution.

In the second situation, there is a 62.5% chance that the data are from a normal distribution. This is a high probability, so we fail to reject the hypothesis that the data are from a normal distribution.

Note that it does not PROVE that the data are from a normal distribution. This is just like a court trial. A verdict of Not Guilty does not PROVE innocence. It just means that there was insufficient evidence to convict.
 
A

Allattar

#3
My question here is with the data that is not normal.

Is it from a similar data set to the data that is normal?
If so why would one look normal and one not normal?

Its time to understand why the p-value is below 0.035. :)

If you have pictures we can help interpret the reasons, but I understand that this was not part of the original question.

But as Miner says both the Normality test from basic statistics and the probability plot from Graphs are running the same test, the Anderson Darling test.
To summarise the differences between the two functions though.
Normality test
Checks for normality, allows use of Anderson Darling, Kolmogorov-Smirnov, or Ryan-Joiner tests for normality.
Doesn't include confidence intervals.
Probability plots
Allows you to specify a distribution to test, see the distribution button
You can use multiple columns, or split data with by variables.
Confidence intervals, more display choices for those multiple graphs.
Plus the ability to tell it which points to include in the plot.
 
E

Ehsan Heidari

#5
As Miner said, There are different way to find "are date is normal or not?" in Minitab. But I get confused!!! for normal date the p-value>0.05. ok? so for first concept when p-value=0.62 the data is normal and for p-value=0.035 the date is non normal!:bonk:
 
A

Allattar

#6
Patterns in the probability plot often reveal why it isnt normal though.

That the data is normal, or not is only half the story.
Is it stable? is the data discrete (eg: at the resolution of the measurement system)

Are their hard boundaries on the data?

What shape does the natural distribution of the data follow?

A P-value answers none of that, but some of it can be inferred from the graph.

The why, is important as it leads you to understand what the data means and what to do with it.
 
E

Ehsan Heidari

#7
Patterns in the probability plot often reveal why it isnt normal though.

That the data is normal, or not is only half the story.
Is it stable? is the data discrete (eg: at the resolution of the measurement system)

Are their hard boundaries on the data?

What shape does the natural distribution of the data follow?

A P-value answers none of that, but some of it can be inferred from the graph.

The why, is important as it leads you to understand what the data means and what to do with it.

Thanks Allattar,
for example: I have 125 data for calculation CPK, before calculation it , I need to sure about normality, so I calculate p-value by using minitab (for example t-test, if the resualt of test was the data is normal I continue calculation CPK, if Not I must to use for "calcaulation CPK with non normal data in minitab"! so in this way I just know are my data normal or not?
 
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