Pareto chart frequently asked questions
What is a Pareto chart?
A Pareto chart is a type of bar chart that displays data in descending order of frequency or size, often combined with a line graph that shows the cumulative total. It’s used to highlight the most important factors in a dataset based on the Pareto principle (80/20 rule), which suggests that 80% of problems are often caused by 20% of the causes.
When should I use a Pareto chart?
Pareto charts are useful when you want to identify and prioritize the most significant factors contributing to a problem or outcome. For example, you might use it to determine which issues or defects contribute the most to customer complaints or production downtime.
How should data be structured to create the Pareto chart?
At a minimum you should have the categorical variable that needs to be plotted. The data can be in a single column where each variable may occur one or more times or the data can be in a frequency table with categorical variable names and their frequencies. An example is shown below.
Table 1
| Categories |
Blue |
Green |
Red |
| White |
Red |
Blue |
Table 2
Category | Frequency |
Blue | 2 |
Green | 1 |
Red | 2 |
White | 1 |
The second method of specifying the data is preferable as it can also include cases where the frequency of a category can be 0.
If the data is formatted as in the first table, the data for analysis can be specified by clicking on Analysis Setup > Data as shown below.
If the data is formatted as shown in the second table, then data for analysis can be specified by clicking Analysis Setup > Data as shown below:
How do I interpret a Pareto chart?
The left bars show the frequency or count of each category, with the largest bars on the left. The cumulative line (on the right) shows the total impact of the categories as they are added together. The goal is to identify the "vital few" categories that make up most of the total impact (typically 80%).
How do we create a horizontal Pareto chart?
Click on Analysis Setup > Setup > Plot Orientation > Horizontal.
An example output is shown below.
How do we add a horizontal line to the Pareto chart?
To add a horizontal line to the chart, click Analysis Setup > Charts and specify the value you want to plot the horizontal line in the textbox for Horizontal Ref Lines. For this example, we have added a line at a frequency = 5.
An example output is shown below:
How do you create the others category if there are too many causes?
Click on Analysis Setup > Setup > Display Categories and specify the percentage above which you want to group the categories into Others. In the example below, we have set the display categories to 80%, so 20% will be grouped into Other.
The resulting Pareto chart is as shown below.
What data do I need to create a Pareto chart?
You need categorical data, typically in the form of frequencies or counts, showing the number of occurrences of various items or events. The data should be sorted in descending order based on frequency or size to highlight the largest contributors.
What’s the difference between a regular bar chart and a Pareto chart?
A regular bar chart displays categories and their values, while a Pareto chart sorts these categories in descending order and also includes a cumulative percentage line, emphasizing which categories are the most impactful.
Can I use a Pareto chart for continuous data?
No, a Pareto chart is most effective with categorical data. For continuous data, other types of charts (like histograms or line graphs) might be more appropriate.
Should I display all categories on the Pareto chart?
While it's possible to display all categories, it's often more effective to focus on the top few categories (the "vital few") that contribute the most. You can exclude or group less significant categories to keep the chart clear and focused.
How do I handle categories with zero values in a Pareto chart?
Categories with zero values should either be excluded from the chart (if irrelevant) or displayed as bars with zero height, depending on the context and your goal for the analysis.
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