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{ "item_title" : "Statistical Methods for Six SIGMA", "item_author" : [" Anand M. Joglekar "], "item_description" : "A guide to achieving business successes through statistical methodsStatistical methods are a key ingredient in providing data-basedguidance to research and development as well as to manufacturing.Understanding the concepts and specific steps involved in eachstatistical method is critical for achieving consistent andon-target performance.Written by a recognized educator in the field, StatisticalMethods for Six Sigma: In R&D and Manufacturing is specificallygeared to engineers, scientists, technical managers, and othertechnical professionals in industry. Emphasizing practicallearning, applications, and performance improvement, Dr. Joglekar?stext shows today's industry professionals how to:Summarize and interpret data to make decisionsDetermine the amount of data to collectCompare product and process designsBuild equations relating inputs and outputsEstablish specifications and validate processesReduce risk and cost-of-process controlQuantify and reduce economic loss due to variabilityEstimate process capability and plan process improvementsIdentify key causes and their contributions to variabilityAnalyze and improve measurement systemsThis long-awaited guide for students and professionals inresearch, development, quality, and manufacturing does not presumeany prior knowledge of statistics. It covers a large number ofuseful statistical methods compactly, in a language and depthnecessary to make successful applications. Statistical methods inthis book include: variance components analysis, variancetransmission analysis, risk-based control charts, capability andperformance indices, quality planning, regression analysis, comparative experiments, descriptive statistics, sample sizedetermination, confidence intervals, tolerance intervals, andmeasurement systems analysis. The book also contains a wealth ofcase studies and examples, and features a unique test to evaluatethe reader's understanding of the subject.", "item_img_path" : "https://covers2.booksamillion.com/covers/bam/0/47/120/342/0471203424_b.jpg", "price_data" : { "retail_price" : "176.95", "online_price" : "176.95", "our_price" : "176.95", "club_price" : "176.95", "savings_pct" : "0", "savings_amt" : "0.00", "club_savings_pct" : "0", "club_savings_amt" : "0.00", "discount_pct" : "10", "store_price" : "" } }
Statistical Methods for Six SIGMA|Anand M. Joglekar

Statistical Methods for Six SIGMA : In R&d and Manufacturing

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Overview

A guide to achieving business successes through statistical methods

Statistical methods are a key ingredient in providing data-basedguidance to research and development as well as to manufacturing.Understanding the concepts and specific steps involved in eachstatistical method is critical for achieving consistent andon-target performance.

Written by a recognized educator in the field, StatisticalMethods for Six Sigma: In R&D and Manufacturing is specificallygeared to engineers, scientists, technical managers, and othertechnical professionals in industry. Emphasizing practicallearning, applications, and performance improvement, Dr. Joglekar?stext shows today's industry professionals how to:

  • Summarize and interpret data to make decisions
  • Determine the amount of data to collect
  • Compare product and process designs
  • Build equations relating inputs and outputs
  • Establish specifications and validate processes
  • Reduce risk and cost-of-process control
  • Quantify and reduce economic loss due to variability
  • Estimate process capability and plan process improvements
  • Identify key causes and their contributions to variability
  • Analyze and improve measurement systems

This long-awaited guide for students and professionals inresearch, development, quality, and manufacturing does not presumeany prior knowledge of statistics. It covers a large number ofuseful statistical methods compactly, in a language and depthnecessary to make successful applications. Statistical methods inthis book include: variance components analysis, variancetransmission analysis, risk-based control charts, capability andperformance indices, quality planning, regression analysis, comparative experiments, descriptive statistics, sample sizedetermination, confidence intervals, tolerance intervals, andmeasurement systems analysis. The book also contains a wealth ofcase studies and examples, and features a unique test to evaluatethe reader's understanding of the subject.

This item is Non-Returnable

Details

  • ISBN-13: 9780471203421
  • ISBN-10: 0471203424
  • Publisher: Wiley-Interscience
  • Publish Date: September 2003
  • Dimensions: 10.28 x 7.14 x 0.86 inches
  • Shipping Weight: 1.79 pounds
  • Page Count: 344

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