Introduction - statistics, SPC and total quality; data collection and graphical summaries; numerical data summaries - location and dispersion; probability and distribution; sampling, estimation and confidence; simple tests of hypotheses - "significance tests"; control charts for process management and improvement; control charts for average and variation; control charts for "single-valued" observations; control charts for attributes and events; control charts - problems and special cases; cusum methods; process capability - attributes, events and normally distributed data; capability - non-normal distributions; evaluating the precision of a measurement system (gauge capability); getting more from control chart data; SPC in "non-product" applications. Appendices: linear combinations of independent variables; linear combination of correlated variables; products and quotients; non-linear functions; dealing with composite functions; other useful standard errors.
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"This book should be compulsory reading for every quality
management consultant, applied statistician, and student of quality
or statistics. It finds the right balance between data analysis and
commonsense management which few people ever strike."
-The Statistician
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