Application of Statistical Process Control (SPC)

Statistical Process Control utilizes sampling and other statistical methods to monitor the quality of an ongoing procedure. The graphical displays such like control charts, run chart, Pareto analysis, etc. provide a basis for deciding whether the variation in the output of a process is because of common cause (randomly occurring variations) or to out-of-the-ordinary assignable causes. Wherever assignable causes are recognized, a decision might be made to adjust the procedure in order to bring the output back to acceptable quality levels.

A goal in the design of sample surveys is to attain a sample that is representative of the population so that precise inferences might be made. Sampling error is the difference between a population parameter and a sample statistic utilized to estimate it. For instance, the difference among a population mean & a sample mean is sampling error. Probability sampling methods (where the probability of each unit appearing in the sampling error), Non-probability sampling methods (which are depend on convenience or judgment instead of on probability) are frequently utilized for cost and time advantages. Sample whether or not is representative is dependent on the judgment of the individuals designing and conducting the survey and not on sound statistical principles. Additionally, there is no objective basis for establishing bounds on the sampling error while non-probability sample has been utilized.

Most governmental & professional polling surveys utilize probability sampling. It might generally be assumed that any survey that reports a plus or minus margin of error has been conducted by using probability sampling. Statisticians have a preference of probability sampling methods and recommend that they be utilized whenever possible. A variety of probability sampling technique is available.