Let's breakdown this result. The figure below is showing the hours of set-up time by machine (four different machines) that set-up the same job repeatedly.

But not necessarily on the same shift, with the same operator, or the same raw material, same tooling - those are all potential input variables creating the variation you see below)

- Each machine had a least one outlier. It would be worth researching what happened in each case. Anything stand out that was different?
- Machine 35077 had the most variation in set-up times and had the highest mean set-up time. However, 35133 has the highest median.
- Machine 35070 and 35069 had similar variance and mean (red dots).
- Machine 35070 has the lowest median and mean.

In summary, nothing glaring stands out. The team should do a deeper dive into the inputs from other FOV's, such as operator, shift, materials, tools, etc. to find the inputs to control.

Click here to learn how to create a Box Plot in Excel.

The picture below is another variant of the Box-Plot from the (c)R Foundation found at http://www.r-project.org.

The R foundation provides free statistical software available as Free Software under the terms of the Free Software Foundation's GNU General Public License in source code form.

**Notched box plots** contain a narrowing of the box around the median. The line where the notches converge is still the median. Notches visually illustrate an estimate on whether there is a significant difference of medians. The width of the notches is proportional to the interquartile range of the sample.

It is still difficult to conclude there is or is not a difference between the medians in data set 6 and 7 but is it pretty clear that the median of groups 1 & 10 are different than 2-9.

The other common variant that shows more information than the standard fixed width box plot is called the **variable width box plot** (like the plot at the top of this page).

However, this is only valuable if comparing more than one box plot since the width is irrelevant if displaying only one box plot.

One common convention is to make the width of the boxes for group of data proportional to the square roots of the number of observations in a given sample.

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