This page provides links to videos to accompany the Analytics Iowa LLC slides on Undergraduate Quality Assurance and Process Improvement located here.
- Quality, Statistics, and Quality Culture
- Process Identification and Analysis
- Measures of Performance and Metrology Basics
- Modeling Measurement
- Measurement and One Sample Inferences Part 1
- Measurement and One Sample Inferences Part 2
- Measurement and Two Sample Inferences Part 1
- Measurement and Two Sample Inferences Part 2
- A Simple Method for Separating Components of Variation in Measurements
- One Way Random Effects Modeling and Measurement
- Inference for One Way Random Effects Models
- The Two Way Random Effects Model and Gauge R&R
- Range-Based Gauge R&R Inference
- Two Way ANOVA Calculations
- ANOVA-Based Gauge R&R Inference
- Gauge Capability Ratios
- Calibration Studies and Inference Based on Simple Linear Regression
- R&R for 0/1 (Go/No-Go) Contexts Part 1 (Modeling)
- R&R for 0/1 (Go/No) Inspection Part 2 (Point Estimates)
- R&R for 0/1 (Go/No) Inspection Part 3 (Application of Elementary Confidence Limits)
- Simple Principles of Process and Engineering Data Collection
- Simple Statistical Graphics for Quality Assurance
- Introduction to Shewhart Control Charting Part 1
- Introduction to Shewhart Control Charting Part 2
- Shewhart Control Charts for Measurements (Variables Data) Part 1
- Shewhart Control Charts for Measurements (Variables Data) Part 2
- EFC and SPM: One Thing Control Charting is Not
- Control Charts for Counts (Attributes Data) Part 1
- Control Charts for Counts (Attributes Data) Part 2
- Patterns on Control Charts Part 1
- Patterns on Control Charts Part 2 and Special Checks/Extra Alarm Rules
- The Average Run Length Concept Part 1
- The Average Run Length Concept Part 2
- What if the Sample Size is 1?
- Process Capability Analysis Part 1 (Normal Plotting)
- Process Capability Analysis Part 2 (Capability Indices)
- Process Capability Analysis Part 3 (Prediction and Tolerance Intervals)
- “Statistical” (Probabilistic) Tolerancing Part 1 (Ideas)
- “Statistical” (Probabilistic) Tolerancing Part 2 (Examples)
- Design and Analysis of Experiments Part 1 (Basics and the One-Way Model)
- Design and Analysis of Experiments Part 2 (One-Way Analyses)
- Design and Analysis of Experiments Part 3 (Two-Way Factorial Studies)
- Design and Analysis of Experiments Part 4 (Fitted Two-Way Factorial Effects)
- Design and Analysis of Experiments Part 5 (Confidence Intervals for Two-Way Analyses)
- Design and Analysis of Experiments Part 6 (p-Way Studies With 2-Level Factors)
- Design and Analysis of Experiments Part 7 (p-Way Fitted Factorial Effects)
- Design and Analysis of Experiments Part 8 (The Yates Algorithm and Prediction for p-Way Studies)
- Design and Analysis of Experiments Part 9 (Inference for p-Way Factorial Studies)
- Design and Analysis of Experiments Part 10 (Fractional Factorial Studies With 2-Level Factors)
- Design and Analysis of Experiments Part 11 (Choice and Aliasing Structure for a Half Fraction)
- Design and Analysis of Experiments Part 12 (Data Analysis for a Half Fraction)
- Design and Analysis of Experiments Part 13 (Choice and Aliasing for Smaller-Than-Half Fraction Studies)
- Design and Analysis of Experiments Part 14 (Data Analysis for Smaller-Than-Half Fractions)
- Design and Analysis of Experiments Part 15 (Some Perspective and a Very-Small-Fraction Example)
The materials on this site may be used without charge for non-commercial personal educational purposes. Any copies made of the materials must bear printed acknowledgment of their Analytics Iowa LLC source.