DUBLIN--(BUSINESS WIRE)--The "Applied Statistics, with Emphasis on Verification, Validation, Sample Size, and Risk Management, in R&D, Manufacturing, and QA/QC" conference has been added to ResearchAndMarkets.com's offering.
The 2-day seminar explains how to apply statistics to manage risks and verify/validate processes in R&D, QA/QC, and Manufacturing, with examples derived mainly from the medical device design/manufacturing industry.
This seminar provides a practical approach to understanding how to interpret and use more than just a standard tool-box of statistical methods; topics include: Confidence intervals, t-tests, Normal K-tables, Normality tests, Confidence/reliability calculations, Reliability plotting (for extremely non-normal data), AQL sampling plans, Metrology (i.e., statistical analysis of measurement uncertainty ), and Statistical Process Control.
Without a clear understanding and correct implementation of such methods, a company risks not only significantly increasing its complaint rates, scrap rates, and time-to-market, but also risks significantly reducing its product and service quality, its customer satisfaction levels, and its profit margins.
Day 1 Schedule
Lecture 1: Regulatory Requirements
Lecture 2: Vocabulary and Concepts
Lecture 3: Confidence Intervals (attribute and variables data)
Lecture 4: Normality Tests and Normality Transformations
Lecture 5: Statistical Process Control (with focus on XbarR charts)
Lecture 6: Confidence/Reliability calculations for Proportions
Lecture 7: Confidence/Reliability calculations for Normally distributed data (K-tables)
Lecture 8: Process Capability Indices calculations(Cp, Cpk, Pp, Ppk)
Day 2 Schedule
Lecture 1: Confidence/Reliability calculations using Reliability Plotting (e.g., for non-normal data and/or censored studies)
Lecture 2: Confidence/Reliability calculations for MTTF and MTBF (this typically applies only to electronic equipment)
Lecture 3: Statistical Significance: t-Tests and related "power" estimations
Lecture 4: Metrology (Gage R&R, Correlation, Linearity, Bias , and Uncertainty Budgets)
Lecture 5: QC Sampling Plans (C=0 and Z1.4 attribute AQL plans, and alternatives to such plans), including OC curves, AQL vs. LQL/LTPD, AOQL, and calculation of acceptance rates.
Lecture 6: Statistically valid statements for use in reports
Lecture 7: Summary and Implementation Recommendations
For more information about this conference visit https://www.researchandmarkets.com/research/rblg4d/2_day_seminar?w=4