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# How to create control charts in Tableau

Updated: Jun 30, 2021

*Definition*

*Definition*

Control chart is a statistical tool used to determine if a manufacturing or business process is in a state of control. Control chart uses standard deviations above and below the mean, which are displayed as bands - with outliers identified using color.

Standard deviation is used to show how far a way data is from the mean. In this chart, the measure of standard deviation is used to identify outliers in the data. (Data points that differ significantly from other observations).

A control chart consists of:

Points representing measurements in samples taken from a process at different times.

The mean of all measurements in the sample.

A center line is drawn at the mean.

The control limits –

**UCL**– the upper control limit and**LCL**– the lower control limit.Signals – Outliers (any point outside the control limits)

**Example of a control chart**

**How to create a control chart in Tableau**

In this article, using __ Sample-Superstore__ data I am going to show you two ways you can create a control chart in Tableau.

__Option one__

__Option one__

Create a simple timeline by dragging **WEEK(Order Date)** to the columns and **SUM(Sales)** to the rows shelf.

Choose Line chart under marks card.

Right-click on the y-axis and add a reference line showing the average value.

Next, right click on the y-axis and add a reference distribution of +2 and -2 standard deviation.

Alternatively, you can also use +3 and -3 or +1 and -1 standard deviation.

Executing these results to.

__Option two__

__Option two__

Create a simple timeline again by dragging **WEEK (Order Date)** to the columns and **SUM(Sales)** to the rows shelf.

Choose circle under marks card.

Create **UCL (upper control limit)** calculation as follows.

*(Note, this calculation computes UCL at 2 standard deviations from the mean. You can change this to 3 standard deviations by simply replacing 2 with 3 in the calculation or use a parameter to empower users choose the number of standard deviations)*

Create **LCL (lower control limit)** calculation as follows.

Next, drag **measure values** to the rows shelf and eliminate all measures from the view except, **LCL**, **UCL** and **SUM(Sales).**

Change the marks card of the second view to a line chart.

Make chart dual axis and synchronize the axis.

Next, right-click on the y-axis and add a reference line showing the average value – just like in the first option of creating a control chart.

Next, lets color the circles – so to empower users easily spot outliers using the following calculation.

Drag the above calculation to the color shelf of the first view.

*(Where you can see that there is one point that falls outside the control limit (one outlier)).*

**Let’s parameterize the control chart.**

Let’s make the control chart dynamic by empowering users choose how many standard deviations to be used in computing the upper and lower control limits.

Create a parameter.

Replace the **2** on the **UCL** and **LCL calculations** with this parameter – **‘Standard deviation’.**

Show the parameter control.

Note, now you can easily recomputed the control limits by selecting the number of standard deviations to be used – on the parameter control.

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