Training Course Syllabus:

Sample Size Justification & Statistical Analysis for Performance Qualification (PQ) Studies

Course Description

Regulatory agencies mandate formal protocols for Performance Qualification (PQ) studies to determine whether products/processes meet the desired requirements. When planning PQ studies, sample size determination is critical to ensure that study results will be meaningful. Methods to determine appropriate sample sizes for various types of problems will be covered.

This 2-day seminar will provide a 12-step process to assist you in writing/reviewing protocols for PQ studies with a focus on sample size justification, acceptance criteria and statistical analysis using Minitab v17. Validation of software will not be covered.

Course Information:

Participants are requested to bring a laptop with Minitab Version 17 software installed.

Learning Objectives:

Upon completing this course participants will be able to:
Determine a Representative Sample for Process Qualification (PQ) study.
Develop product/process acceptance criteria statements
Determine appropriate Sample Size to meet PQ acceptance criteria
Understand how to Analyze PQ data
Understand how to calculate and interpret statistical tolerance limits
Determine and verify the appropriate distribution of the data
Interpret probability plots
Apply normalizing transformations
Handle censored data and mixed failure modes.

DAY 01(8:30 AM - 4:30 PM)

Registration Process - (8:30 am till 8:45 am)
Lecture 1: Introduction
Course Objectives
Selecting Representative Sample
Confidence Level Definition
General Flow Chart for 12-step Protocol Development
Lecture 2: Sample Size Determination for Performance Qualification Study
General Purpose
Acceptance Criteria
Attribute (Pass/Fail) Response
Censored (Variable) Response
Lecture 3: Non-Censored (Variables) Response
Tolerance Limits Defined
One-Sided vs Two-Sided Limits
Normality Assumptions
Nonparametric Tolerance Limits

DAY 02(8:30 AM - 4:30 PM)

Lecture 4: Analyzing PQ Data using Minitab
Statistical Tolerance Limits
Confidence Level
Percentage of Population captured
Lecture 5: Distribution Fitting using Graphical Methods
Histograms
Boxplots
Probability Plots
Lecture 6: Statistical Tests for Distribution Fit
Anderson-Darling
Ryan-Joiner
Kolmogorov-Smirnov
Lecture 7: Normalizing Transformations
Lognormal
3-Parameter Lognormal
Box-Cox
Johnson
Lecture 8: “Non-Normal” Statistical Tolerance Limits
Weibull
3-Parameter Weibull
Smallest Extreme Value
Mixed populations or multiple failure modes

Seminar Summary:

A 12-step process to assist you in writing/reviewing protocols for PQ studies with a focus on sample size justification, acceptance criteria and statistical analysis using Minitab v17. Validation of software will not be covered. (see full course description)

print this agenda