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In statistical quality control, thep-chart is a control chart used to monitor the proportion of nonconforming units in a sample, where the sample proportion nonconforming is defined because the ratio of the quantity of nonconforming units to the sample size, n.

The p-chartonly accommodates "pass"/"fail"-type inspection as determined by one or more go-no-go gauges or tests, effectively applying the specifications to the data before they're plotted on the chart.

A p- chart is to be developed,

Based on the table,

$\begin{array}{l}\stackrel{¯}{p}=\left(\frac{\text{Sumofallunsatisfactorymeals}}{\text{SampleSize}×\text{Numberofdayssurveyconducted}}\right)\\ \stackrel{¯}{p}=\left(\frac{600}{1000+10}\right)=0.06\end{array}$

$\begin{array}{l}\text{Standarddeviation}{S}_p=\sqrt{\frac{\stackrel{¯}{p}(1−\stackrel{¯}{p})}{n}}\\ =\sqrt{\frac{0.06(1−0.06)}{1000}}\\ =0.00751\end{array}$

Given a confidence interval of (Z = 95.5%)

Z – Score for a confidence interval of 95.5% = 1.96

Control limit of p- chart:

Upper control limit (UCL) = $\stackrel{¯}{p}+\mathrm{Ζ}×S_P$

(UCL) = 0.06+1.96 * 0.00751

(UCL) = 0.07472

Lower control limit (UCL) = $\stackrel{¯}{p}−\mathrm{Ζ}×S_P$

(LCL) = 0.06-1.96*0.0075

(LCL) = 0.04528

$\text{p}=(\text{numberofunsatisfactorymeals}/\text{samplesize})$

P- Chartis drawn as below:

From the p-chart, it can observe that some points are out of control limit based on a 95.5% confidence interval. Therefore, the process is out of statistical control.