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In the words of Dr. K Ishikawa "modern quality control, or statistical quality control (SQC), as we know it today, began in the 1930s with the industrial application of the control chart invented by Dr. W A Shewhart of the Bell Laboratories."

The second world war was the catalyst that made the control chart's application possible to various industries in the United States when mere reorganization of production systems proved inadequate for meeting the exigencies of semi-wartime and wartime conditions. However by utilising quality control, the United States was able to produce military supplies inexpensively and in large quantity. The wartime standards published at that time came to be known as Z-1 standards.

England also developed quality control at a relatively early date. It had been the home of modern statistics, the application of which is evident in the adoption of British Standards 600 in 1935 based on E S Pearson's statistical work. Later, U.S. Z-1 Standards were adopted in their entirety as British Standards 1008. Other standards were also formulated and put into use in England during the war years.

America's wartime production was quantitatively, qualitatively, and economically very satisfactory, owing in part to the introduction of statistical quality control, which also stimulated technological advances. One might even speculate that the Second World War was won by quality control and by the utilization of modern statistics. Certain statistical methods researched and utilized by the allied powers were so effective that they were classified as military secrets until the surrender of Nazi Germany.

From the above brief account, it is clear that application of control chart and other statistical methods played a key role in achieving the objectives of industrial production. Therefore SQC can be stated as "Application of Statistical Concepts and Techniques in Control of Quality in all areas."

These statistics have five stages of statistical integrity

1. Collection of data
2. Organisation of data
3. Presentation of data
4. Analysis of data
5. Interpretation of data

Correct and factual data are a must for correct interpretation and sound decision making.

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