Six Sigma Tool Navigator: The Master Guide for Teams

2017-07-07 02:10:07

AKA

Box and Whisker Plot

Classification

Analyzing/Trending (AT)

Tool description

The box plot illustrates a distribution of data showing location and spread of values, skewness, and possible outliers (extremely high or low scores). Although a box plot is less detailed than a histogram, it is quite useful in that it will display extreme variations in the data plotted.

Typical application

To identify outliers in a data set.

To compare groups of data for significant differences in patterns.

To check for improvement in data after a process change has been made.

Problem-solving phase

	Select and define problem or opportunity
→	Identify and analyze causes or potential change
	Develop and plan possible solutions or change
	Implement and evaluate solution or change
→	Measure and report solution or change results
	Recognize and reward team efforts

Typically used by

1	Research/statistics
	Creativity/innovation
3	Engineering
	Project management
2	Manufacturing
	Marketing/sales
	Administration/documentation
	Servicing/support
	Customer/quality metrics
	Change management

links to other tools

before

Data collection strategy

Stem and Leaf Display

Observation

Dot Diagram

Sampling Methods

after

Variance Analysis

Problem analysis

Process analysis

Potential problem analysis (PPA)

What-If Analysis

Notes and key points

Use the follwing equation to calculate ranks for quartiles:

For this example:

– Median rank=

– Rank of lower quartile (L.Q.)=

– Rank of upper quartile (U.Q.)= (n + 1) − L.Q. = (24 + 1) − 6.5 = 18.5

To identify outliers use the following:

– Check for larger data values:

– Therefore defect scores 61 and 65 are outliers at the high end of the distribution.

– Check for smaller data values:

– The lowest data value = 5; therefore there is no outlier at the low end of the distribution.

Step-by-step procedure

STEP 1 Data is collected and identified by recording the collection period, data source, and exact description of what is supposed to be measured. See example Operator Defects Covering Four 6-Day Weeks.

STEP 2 A table of rank-ordered data is constructed and median, lower and upper quartiles calculated. See notes and key points for the calculations used in this example.

STEP 3 A box plot is constructed as shown. Ensure that outliers are identified and marked.

STEP 4 Check all data values, box plot dimensions and outlier values, date the plot, and make final notes on the pattern or variation of the data.