Line Plots
Investigate the Factors that Affect Your Bottom Line
If you think about a process that's important to your success, be it baking perfect loaves of bread or handling tech support calls with ease, you know that any number of factors have the potential to make or break its outcome.
For example, a change in suppliers for a key component in bulletproof glass could affect product strength. Similarly, one method of laminating this glass might be better or worse than another.
But even more complicated to consider is how these factors might interact. In this case, glass made with material from supplier "A" might be strongest when produced with the first laminating method, while glass utilizing material from supplier "B" might be best when constructed with the second laminating method.
Becoming aware of these kinds of interactions is an important first step in maintaining quality when conditions change. But where do you begin? You can start by creating a Minitab line plot.
Two faces of the line plot
Minitab's Line Plot is flexible enough to help you find interactions and response patterns whether you have 2 factors or 20. But while the graph is always created the same way, such changes in scale produce two seemingly distinct types of graph.
With just a few groups…
The focus is on finding interaction effects. Here, a paint company looking to improve the performance of its products begins its investigation with a line plot that finds a strong interaction between spray paint formulation and the pressure at which it's applied.
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An interaction is present where the lines are not parallel. |
With many groups…
The focus is on identifying deviations from an expected response profile. Common in the chemical industry, this is sometimes called a profile graph. Here, a comparison of chemical profiles of a drug produced on three different manufacturing lines begins with a line plot. | 
Any profile that deviates from the established pattern could suggest quality problems with that production line, but these three profiles look quite similar. |
More possibilities to explore
If you're already an avid Minitab user, the above examples may be familiar. In its various incarnations, the line plot is similar to the interaction plot, "Calculated X" plots used in PLS, and even time series plots that appear with more advanced analyses. But line plot gives you many more options for exploring your data. Here's just one example:
A line plot of the mean sales from a call center shows very little interaction between the script being used for the call and whether the had been given sales training because the lines are parallel. |  |
But because line plot will allow us to examine functions other than the mean, we can see that there is in fact an interaction effect in terms of standard deviation - the lines are not parallel. For some reason, the variability in sales seems to be affected by the combination of script and training. |  |
How to create a line plot in Minitab
Creating a line plot in Minitab is simple. For example, suppose your company makes seat belts. You're concerned about the mean strength of webbing woven on three looms with raw materials from two suppliers.
Because you're examining only two factors - loom and supplier - a With Symbols option is appropriate. Use Without Symbols options when you have many groups to consider – symbols may clutter the graph. Within these categories, you have your choice of data arrangement. - Choose Graph > Line Plot > With Symbols, One Y.
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Now enter the variables you want to graph. Note that Line Plot allows you to graph a number of different functions apart from the mean. - In Graph variables, enter 'Break Strength.'
- In Categorical variable for X-scale grouping, enter Loom.
- In Categorical variable for legend grouping, enter Supplier. Click OK.
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| The line plot shows a clear interaction between the source of the seat belt material and the loom being used to weave it into webbing. Your QA team feels this unexpected interaction is worth investigating. |  |
Putting line plots to use
The line plot is an excellent exploratory tool allowing a first glimpse into the data behind your processes. The line plot may highlight the variables and interactions worth exploring. Its powerful graphing features also allow you to analyze subsets of your data or to graph different functions of your measurement variable like standard deviation or count.
The line plot is similar to a number of graphs you might associate with specific statistical analysis, such as the interaction plots used in the context of DOE or ANOVA analyses. But while the function of line plots may be similar, their simplicity makes them an especially appropriate starting point.
All of this makes the line plot an incredibly agile tool in the quest to better understand your processes.