Distribution analysis for variable data is one of the critical analysis that help us understand how much
variation exists in the data. This in turn helps us understand how wide the process is and whether it falls within the specification limits.
There are several tools for studying distribution of variable data. The tools listed below are some of the popular ones:
1. Histogram
2. Stem and Leaf plot
3. Dot plot
4. Box plot
Histogram being the most popular to understand the nature of distribution of variable data. Dot and Stem & Leaf plot are more detailed versions for analyzing data distribution.
Box plots (also known as Box and Whisker plot) are used to compare distributions. Example for using a box plot would be to compare machine performance.
The figure below shows a comparison of the 4 tools.
We would love to hear which of the above tools have you used for analyzing distribution of variable data. Write to us at info@sybeq.com
variation exists in the data. This in turn helps us understand how wide the process is and whether it falls within the specification limits.
There are several tools for studying distribution of variable data. The tools listed below are some of the popular ones:
1. Histogram
2. Stem and Leaf plot
3. Dot plot
4. Box plot
Histogram being the most popular to understand the nature of distribution of variable data. Dot and Stem & Leaf plot are more detailed versions for analyzing data distribution.
Box plots (also known as Box and Whisker plot) are used to compare distributions. Example for using a box plot would be to compare machine performance.
The figure below shows a comparison of the 4 tools.
No comments:
Post a Comment