When dealing with non normal data should we try to convert data using transforamtion or Use Capability Analysis (Nonnormal) available in Minitab .

Which is a better way of doing it.

Alok

First thing is trying to understand why your data is non-normal. You can try to plot it in a time line to see for patterns, etc.

Then MINITAB offers two options:

1. Convert the data (Box Cox available in Normal Capability dialog) and analyze it. Be warned that your limits and specs will change, but you'll get the info.

2. Identify the distribution first using the Individual Distribution Identification and then use the Non-normal capability analysis.

MINITAB recommends the first option.

Good luck.

First thing is trying to understand why your data is non-normal. You can try to plot it in a time line to see for patterns, etc.

Then MINITAB offers two options:

1. Convert the data (Box Cox available in Normal Capability dialog) and analyze it. Be warned that your limits and specs will change, but you'll get the info.

2. Identify the distribution first using the Individual Distribution Identification and then use the Non-normal capability analysis.

MINITAB recommends the first option.

Good luck.

pabloquintana is correct about the two options. I wanted to comment on the first paragraph.

Some processes may indeed be non-normal because the process is out-of-control. However, some processes are inherently non-normal. Some good examples of this are characteristics with a boundary condition (physical limit) such as zero. You cannot have a parallelism or flatness less than zero. Therefore, the closer you approach zero, the more non-normal the process will typically appear, while flatness distributions situated at a distance from zero may appear quite normal. A process that uses a physical stop to control a dimension will typically have a non-normal distribution because you cannot get a dimension past the stop, but you can get any dimension short of the stop. Screw machines were a classic example of this situation.

In summary, check the obvious causes such as out-of-control, but do not think that a non-normal process is always caused by that. It may be the "normal" condition. If you can provide more information on the nature of the process and the characteristic in quetions, we may be able to comment on the expected distribution.