Use P charts to study the proportion of defectives in each sample and determine whether or not the process is in control.

·    An in-control process exhibits only random variation in the proportion of defectives per sample.

·    An out-of-control process exhibits nonrandom variation in the proportion of defectives per sample, which may be due to the presence of special causes.

A defective is a product or service in which a nonconformity (or flaw) renders the product or service unusable. Examples of defectives include broken light bulbs, late deliveries, unanswered calls, and blown fuses.

Use P charts when your sample sizes vary.

If your data exhibit overdispersion or underdispersion a Laney P' chart may more accurately distinguish between common cause variation and special cause variation.

A telephone service center wants to assess whether its call answering system is in control. The total number of incoming calls and number of unanswered calls were recorded for 21 days. Each unanswered call is a defective. Because the number of incoming calls varies daily, a P chart should be used to analyze the data.

Data: Telephone.MTW (available in the Sample Data folder).