Provides a static picture of the location and spread of the Y variable (the process output) by showing the minimum and maximum values, first quartile (25% of points are less than this value), third quartile (75% of points are less than this value), median (or mean), and potential outliers. If you also include a categorical X variable, you can look at the location and spread of the Y at each level (for example, factor setting) of the X variable.
|When to Use||Purpose|
|Mid-project||The first rule in data analysis is to always plot your data before running any statistical tests. The boxplot is a logical choice for comparison tests where you are looking at what happens to the process output under various conditions, such as changes to a process input.|
|Mid-project||Assess if an input (X) has an impact on the process mean or process variation and help eliminate noncritical X's from consideration.|
|Mid-project||Identify levels (settings) of the process input that have the desired impact on the output mean or variation.|
|Mid-project||Communicate the effects of process inputs on the process output to project stakeholders.|
Numeric Y, with optional discrete X (categories for comparison).