Pareto Charts or Pareto Plots are basically a ranked order histogram that will most likely include cumulative percentage line. I'll demo this in JMP using the Failure sample data set.
Pareto Plots are extremely useful for analyzing what problems need attention first because the taller bars on the chart, which represent frequency, clearly illustrate which variables have the greatest cumulative effect on a given system.
The Pareto Plot provides a visualization of the Pareto principle, a theory maintaining that 80% of the output in a given situation, or system, is produced by 20% of the input.
Pareto Plot Demo
With the Failure.jmp sample data table opened in JMP will select
Select Analyze > Quality and Process > Pareto Plot.
Select failure and click Y, Cause or Drag it over.
This column lists the causes of failure and is the variable that you want to inspect.
Select N and click Freq or Drag it over
This column list the number of times each type of defect occurred.
The left axis represents the count of failures, and the right axis represents the percent of failures in each category.
The bars are in decreasing order with the most frequently occurring failure to the left.
The curve indicates the cumulative failures from left to right.
Now select Label Cum Percent Points from the red triangle menu next to Pareto Plot.
Note that Contamination accounts for approximately 45% of the failures.
And if we include Oxide Defect and Misc those 3 account for 80% of Failures.
Use the Failure sample data and explore the additional red triangle settings such as Threshold of Combined Causes.