P charts are tools of statistical quality control which may be applied in different fields. In actuality, P charts are widely-applied and they have proved to be quite successful due to their high reliability and effectiveness. Moreover, they are implemented in new fields, where the statistical quality control is important.
In actuality, P charts are applied successfully in the online documentation. They help to maintain online documentation properly and process the information effectively. P charts help to minimize the risk of error while working with a large amount of data online (Anderson, Sweeney, Williams, 7). They help to classify online documentation and sort it out respectively to users’ needs and wants.
Furthermore, P charts are applied successfully in industrial statistics. They are used to control and to monitor the proportion of nonconforming units in a sample. In such a way, they help to increase the quality of the industrial production minimizing the share of nonconforming units (Boneau, 52). The implementation of P charts in industrial statistics has expanded the scope of application of P charts and made them really efficient to control and to maintain the high quality of production.
In fact, P charts can be applied successfully in different fields, including health care. For instance, P charts are applied successful to measure the quality of birth weight (Moore, 20). P charts allow sorting out nonconforming units in subgroups. As a result, health care professionals use P charts to find out low birth weight cases to conduct the detailed statistical analysis and to make essential improvement.
Thus, the scope of application of P charts is wide. P charts are used successfully in different fields.