A control chart is a graphical tool to help determine if a process may be exhibiting non$-$random variation that needs to be investigated. If non$-$random variation is present, the process is said to be "out of control" otherwise it is said to be $"$in control." The following figure shows a control chart for a production line that fills boxes of cereal. Based on past data, we can calculate the mean weight of a box of cereal when the process is in control. The mean weight is $16\mathrm{.}05$ ounces. We can also calculate control limits$,$ an upper control limit $($UCL$)$ and a lower control limit $($LCL$).$ New samples are collected over time and the data indicates that the process is in control so long as the new sample weights are between UCL and LCL$.$ As shown in the chart, only sample $5$ is outside of the control limits$.$

A control chart has a horizontal axis labeled "Sample Number" with values from $1$ to $10$ and a vertical axis labeled "Sample Mean x bar" with values from $15\mathrm{.}84$ to $16\mathrm{.}22.$ The control chart contains $3$ horizontal lines and a series of $10$ points connected by line segments. The $3$ horizontal lines' labels and approximate heights are: $"$LCL $=15\mathrm{.}93"$: $15\mathrm{.}93$; "Process Mean": $16\mathrm{.}05$; "UCL $=16\mathrm{.}17"$: $16\mathrm{.}17.$

$1$ point is below LCL $=15\mathrm{.}93$ at approximately $(5,15\mathrm{.}88).$

$5$ points are between LCL $=15\mathrm{.}93$ and Process Mean at approximately $(2,15\mathrm{.}96),(4,15\mathrm{.}99),(6,16\mathrm{.}03),(7,16\mathrm{.}03),(9,15\mathrm{.}98).$

The point $(10,16\mathrm{.}05)$ is directly on Process Mean.

$3$ points are between Process Mean and UCL $=16\mathrm{.}17$ at approximately $(1,16\mathrm{.}12),(3,16\mathrm{.}06),(8,16\mathrm{.}08).$

The point $(5,15\mathrm{.}88)$ is labeled "Process out of control."

Is the control chart an example of descriptive, predictive, or prescriptive analytics?

descriptive analytics

predictive analytics

prescriptive analytics