Descriptive statistics provide a concise summary of data. You can summarize data numerically or graphically. For example, the manager of a fast food restaurant tracks the wait times for customers during the lunch hour for a week and summarizes the data. With the use of statistical numbers and graph, the manager will be able understand better the weekly pattern of waiting times, and implement actions to reduce these, ultimately increasing customer satisfaction.
Inferential statistics use a random sample of data taken from a population to describe and make inferences about the population. Inferential statistics are valuable when it is not convenient or possible to examine each member of an entire population. For example, it is impractical to measure the diameter of each nail that is manufactured in a mill, but you can measure the diameters of a representative random sample of nails and use that information to make generalizations about the diameters of all the nails produced.
A Measurement Systems Analysis considers the following:
Statistical Process Control is an industry-standard methodology for measuring and controlling quality during the manufacturing or service operation process. Quality data in the form of Product or Process measurements are obtained in real-time during manufacturing or service process. This data is then plotted on a graph with pre-determined control limits. Control limits are determined by the capability of the process, whereas specification limits are determined by the client's needs. The concepts of Statistical Process Control (SPC) were initially developed by Dr. Walter Shewhart of Bell Laboratories in the 1920's, and were expanded upon by Dr. W. Edwards Deming, who introduced SPC to Japanese industry after WWII. After early successful adoption by Japanese firms, Statistical Process Control has now been incorporated by organizations around the world as a primary tool to improve product quality by reducing process variation.
Process capability compares the output of an in-control process to the specification limits by using capability indices. The comparison is made by forming the ratio of the spread between the process specifications (the specification "width") to the spread of the process values, as measured by 6 process standard deviation units (the process "width").
This training series is ideal for all functions related to operations, quality, productivity, process engineering, operational excellence, data analytics, metrics monitoring and reporting, and similar areas where a lot of data are monitored, measured, analyzed, and utlimately used for decision making, either as part of a project (i.e. Six SIgma) or regular data reports.