Statistics for Quality Engineering
Many Quality Engineers join the workforce with technical understanding of the products without the statistical understanding of product variability. The FDA´s findings of deficiencies concerning sample size, gage studies, statistical process control and other statistical issue indicate the agencies expect definitive evidence that statistics are properly applied. Case studies and example from FDA 483 findings will be presented.
The cost of non-compliance is therefore more than that of compliance. Are you in compliance with the FDA regulations?
In this two day workshop conference you will learn the different statistical tools necessary to comply with global agencies expectations. Through case study analysis we will examine best practices to provide thoughts and ideas to develop or improve the performance of your current system. Additionally, case studies will explore how your management practices can help or hurt your liability that arises from nonconformance with regulators and Auditors.
Upon completing this course participants should:
Understand measures of location and dispersion of their data
Utilize hypothesis testing and confidence intervals to explain statistical differences.
Understand Analysis of Variance techniques.
Perform regression analysis for stability studies.
Design and analyze experiments using DOE
Understand different types of measurement system analysis studies and when to use them.
Problem solving methods to help you assess which is best for your situation
Develop successful implementation plans
Perform risk assessments effectively
DAY 01(8:30 AM - 4:30 PM)
Registration Process - (8:30 am till 9:00 am)
Lecture 1: Data and Graphical Analysis
Lecture 2: Hypothesis Testing
Lecture 3: Confidence Testing
Lecture 4: ANOVA
DAY 02(8:30 AM - 4:00 PM)
Lecture 5: Regression
Lecture 6: DOE
Lecture 7: MSA
Lecture 8: Sample Size
Lecture 9: Capability Analysis