Speaker Profile


John N. Zorich

Statistical Consultant & Trainer, Ohlone College & SV Polytechnic

John N. Zorich has spent almost 40 years in the medical device manufacturing industry; the first 20 years were as a "regular" employee in the areas of R&D, Manufacturing, QA/QC, and Regulatory; the next 15 years were as a consultant in the areas of QA/QC and Statistics. These last few years were as a trainer and consultant in the area of Applied Statistics only. His consulting clients in the area of statistics have included numerous start-ups as well as large corporations such as Boston Scientific, Novellus, and Siemens Medical.

His experience as an instructor in applied statistics includes having given annual 3-day seminars for many years at Ohlone College (San Jose CA), and previously having given that same course for several years for Silicon Valley ASQ Biomedical. He's given numerous statistical seminars at ASQ meetings and conferences. And he creates and sells validated statistical software programs that have been purchased by more than 110 companies, world-wide.

  •  Wednesday, August 28, 2019
  • 10:00 AM PDT | 01:00 PM EDT,
  • 90 Minutes
  • $150.00
Better Alternatives to AQL Sampling Plans for Risk Management in Incoming QC

The pros and cons of the 2 most widely used sampling plans (ANSI Z1.4, and Squeglia's C=0) are examined in detail, focusing especially on the weaknesses of such plans in regards to meeting regulatory requirements. Real-world examples are provided for how using such sampling plans leads to production of non-conforming product.

  •  Wednesday, September 11, 2019
  • 10:00 AM PDT | 01:00 PM EDT,
  • 60 Minutes
  • $150.00
Process Validation: Statistical Justification for Sample Size and the Use of Only 3 Lots

This webinar explains how to choose and justify a sample-size for Lots that are included in Process Validation studies.

  •  Wednesday, September 25, 2019
  • 10:00 AM PDT | 01:00 PM EDT,
  • 2 Hours
  • $190.00
2-Hour Virtual Seminar on Valid Statistical Rationales for Sample Sizes

This webinar explains the logic behind sample-size choice for several statistical methods that are commonly used in verification or validation efforts, and how to express a valid statistical justification for a chosen sample size.

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  • Recorded
  • View Anytime
  • 90 Minutes
  • $189.00
Better Alternatives to Sampling Plans

The webinar begins with an examination of ISO and FDA regulations and guidelines regarding the use of statistics, especially in regards to Sampling Plans. The pros and cons of the 2 most widely used sampling plans (ANSI Z1.4, and Squeglia's C=0) are examined in detail, focusing especially on the weaknesses of such plans in regards to meeting regulatory requirements. Real-world examples are provided for how using such sampling plans leads to production of non-conforming product.

  • Recorded
  • View Anytime
  • 90 Minutes
  • $189.00
Introduction to SPC (Statistical Process Control)

Manufacturing involves an attempt to produce items that as closely as possible meet design specifications (e.g., size, strength, etc.). However, all production processes exhibit variation - that is, no two items are identical. What method can we use to reduce such variation? The classic and still most widely used method is called SPC or "statistical process control".

  • Recorded
  • View Anytime
  • 90 Minutes
  • $189.00
Statistical Analysis of Gages

The webinar begins with an examination of the fundamental vocabulary and concepts related to metrology. Topics include: accuracy, precision, calibration, and "uncertainty ratios". Several of the standard methods for analyzing measurement variation are then described and explained, as derived from AIAG's Measurement System Analysis reference book. The methods include: Gage R&R (ANOVA method, for 3 gages, 3 persons, 3 replicates, and 10 parts), Gage Correlation (for 3 gages), Gage Linearity, and Gage Bias.

  • Recorded
  • View Anytime
  • 90 Minutes
  • $189.00
Confidence-Reliability Calculations and Statistically Valid Sample Sizes

The webinar begins with a discussion of relevant regulatory requirements, as motivation for calculating "confidence/reliability". Then, some vocabulary and basic concepts are discussed.

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