Pattern hex
School of Six Sigma


When it comes to see­ing how process­es change over time, the abil­i­ty to graph data can be invalu­able, espe­cial­ly for con­tin­u­ous improve­ment prac­ti­tion­ers. They can even help empha­size dif­fer­ent attrib­ut­es of the same data.

But with so many graphs out there, how do you know if you’re using the best Lean or Six Sig­ma chart for your par­tic­u­lar data set?

This series of videos will answer that ques­tion for you.

What Do You Need to Know for Our Six Sigma Graphs Course?

Before we dive into the top Lean and Six Sig­ma graphs for busi­ness, con­sid­er this hypo­thet­i­cal scenario.

Your man­ag­er wants to gain a bet­ter idea of how a plas­tic mold­ing process is per­form­ing and asks for your help. She’s par­tic­u­lar­ly inter­est­ed in how con­sis­tent the weights of these plas­tic parts are.

To help you get start­ed, she pro­vides you with weight data of 200 parts that were ran­dom­ly sam­pled and weighed over the last few days of pro­duc­tion. With so much raw data to sift through, it can be dif­fi­cult to come to any accu­rate con­clu­sion. In this case, you decide graph­ing the data is the best way to make sense of it.

And though there are a num­ber of graphs to choose from, you set­tle on cre­at­ing a stan­dard his­togram. From this graph, you notice that the data seems to form a bell shape, which means the sam­ple mean is rough­ly four pounds. 

From this one graph alone, you are in a much bet­ter posi­tion to explain how this par­tic­u­lar process is per­form­ing to your manager.

Graphs on ipad

What You’ll Learn with Graphs

In this video, you’ll learn about the most pop­u­lar types of graphs used by Lean and Six Sig­ma prac­ti­tion­ers, as well as how and when to use them.

Keep in mind — many graphs are designed to work with vari­able data while oth­ers are designed to work with attribute data. And some of these graphs work bet­ter with larg­er sam­ple sizes, while oth­ers per­form well with small­er sam­ple sizes.

Pareto Chart

A Pare­to chart is a type of bar graph that has been sort­ed in order of decreas­ing fre­quen­cy, and often depicts which sit­u­a­tions are more sig­nif­i­cant. This chart gets its name from Ital­ian econ­o­mist and social­ist, Vil­fre­do Pare­to, who observed in 1906 that approx­i­mate­ly 80% of the land in Italy was owned by 20% of the pop­u­la­tion. Busi­ness con­sul­tants such as Joseph Juran lat­er applied this Pare­to Prin­ci­ple to qual­i­ty con­trol by dis­cov­er­ing that 80% of all effects come from 20% of the causes.

Gen­er­al­ly, Pare­to charts are used to iden­ti­fy improve­ment oppor­tu­ni­ties, par­tic­u­lar­ly when any kind of defect infor­ma­tion is encountered.

Pie Charts

One of the most pop­u­lar graphs on this list, pie charts are intend­ed to dis­play the rel­a­tive fre­quen­cy of count data, or whole num­bers or inte­gers. In oth­er words, pie charts are best for com­par­ing the rela­tion­ship of parts to a whole.

When­ev­er you hear per­cent of…” or part of… ‚” that’s an indi­ca­tion that a pie chart could meet your needs.


If you want to bet­ter under­stand the shape and spread of vari­able data, or data that is acquired through mea­sure­ments, his­tograms are the way to go. The hor­i­zon­tal, or X axis of a his­togram, rep­re­sents the sale of a data. This scale is then divid­ed into equal inter­vals called bins. These bins act as buck­ets that hold data with­in a spe­cif­ic range.

When­ev­er data is nor­mal­ly dis­trib­uted, his­tograms will gen­er­al­ly have a bell shape to them, like in the exam­ple men­tioned ear­li­er. The bell shape con­veys that the data is fair­ly sym­met­ric since each side is essen­tial­ly a mir­ror image of the oth­er side.

While it’s pos­si­ble to cre­ate his­tograms with small­er sam­ple sizes, they may not be a good rep­re­sen­ta­tion of the true process. A good best prac­tice is hav­ing 50 or more data points to ensure accuracy.

Dot Plot

As its name implies, dot plots are graph­i­cal dis­plays of data using dots. This type of graph is rec­om­mend­ed when deal­ing with small sam­ple sizes of vari­able data.

While the dot plot may not help us under­stand the over­all shape of the data, we can dis­cov­er whether our data seems to be clus­tered in a spe­cif­ic region or whether we have out­liers or unusu­al data that war­rants fur­ther investigation.

Individual Value Plot

Instead of sum­ma­riz­ing the results into box­es and whiskers like dot plots, indi­vid­ual val­ue plots rep­re­sent each val­ue of data indi­vid­u­al­ly as a dot.

With these types of graphs, our ver­ti­cal, or Y axis, rep­re­sents the scale of the data. Each data point is then plot­ted accordingly.

Box Plot

Often used in explorato­ry data analy­sis, box plots help us see larg­er pat­terns in the dis­tri­b­u­tion of vari­able data.

Although box plots may seem anti­quat­ed in com­par­i­son to a his­togram, they have the advan­tage of tak­ing up less space, which is use­ful when com­par­ing dis­tri­b­u­tions between mul­ti­ple groups or datasets.

Time Series Plot

A time series plot allows you to dis­play data col­lect­ed in a time sequence from any process. This can help you track how your data is trend­ing over time and if the data points are exhibit­ing any patterns.

Control Chart

Con­trol charts, also known as She­whart charts or process behav­ior charts, are used to iden­ti­fy whether a man­u­fac­tur­ing or busi­ness process is in a state of control.

In this case, upper and low­er con­trol lim­its are added in order to help you under­stand the vari­a­tion in the process.