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## About this lesson

When the process or problem data set has multiple characteristics, there are a set of graphing techniques that can show these effects. Although more complex than the basic techniques, they are easy to use and create a picture of the data set.

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## Quick reference

### Graphing Of Complex Data

When the process or problem data set has multiple characteristics, there are a set of graphing techniques that can show these effects. Although more complex than the basic techniques, they are easy to use and create a picture of the data set.

### When to use

Graphical analysis is an excellent way to visualize patterns and key insights from data. It is also a great way to communicate data to the Lean Six Sigma team and stakeholders. These techniques are applicable for use with multivariate data.

### Instructions

Graphical analysis creates a picture of the data which helps to put the data into context. It makes it possible to display a great deal of data on one graph and the patterns in the data can reveal problems and correlation between process parameters and factors. Three graphs are often used with multivariate data.

#### Horizontal Bar Chart

The horizontal bar chart is an excellent technique with attribute data. It is similar to the vertical bar charts but with the bars running horizontally. The categories of the data are shown on the vertical axis and are represented by rows on the chart. The horizontal axis is the count of instances for the categories – not a time scale. The rows of data are normally sorted so that the longest data is at the top and shortest at the bottom. Unlike the vertical bar chart, there is no limit to the number of rows shown on the chart.

#### Pie Chart

The pie chart is a graphical illustration of relative percentages of attributes or categories. The width of each slice of the pie shows the percentage associated with that attribute value. Pie charts are frequently used in comparison such as comparing different pies for different locations or different products. I have frequently used them for comparing before and after conditions in the product or process being improved.

#### Box Plots

The box plot chart is normally used to present a family of box plots. Each box plot represents a data set such as for multiple locations, multiple products, or multiple customers. The box plot requires variable data. The data values are sorted from largest to smallest. Five points in the data set are used to create the plot. The minimum value, the maximum value, the midpoint (median value), the value at the 25% point in the sorted data and the value at the 75% point in the data. A horizontal line is created that is the length of the spread of the data – one end is the minimum and one the maximum. A box is placed over the line that is located so that the 25% point is one side and the 75% point is the other side. Finally the median value is shown with a line through the box.

#### Data Tables

Multivariate data items can also be shown in a table. The table is structured so that each row is a data item. Each column represents one of the categories of data – either variable or attribute. Normally, the table will be sorted from highest to lowest value using data found in one of the columns. Large tables of numbers can be difficult to read, so the units for numeric data should be chosen so that most data values have two or three digits.

### Hints & tips

- When creating a horizontal bar chart with a large number of rows (40 or 50) it is often helpful to use multiple colors for the bars. However, create a pattern of colors and maintain that pattern so that people won’t think that the color is also a data attribute.
- Don’t use time-based data items with a horizontal bar chart. People try to make the horizontal axis a timeline instead of a count of instances.
- Typically limit the pie chart to about six or seven slices otherwise some slices are so small they are unreadable.
- Box plots provide a visual cue for whether data sets are similar. If you are not sure about similarity, you will need to do a statistical analysis.
- Graphs are supposed to help to understand the data. Don’t let your graphs become so complex that they are confusing to read.

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