Click here
to go
(workshops, classes, seminars, and webinars)
to be given by John Zorich
end of list of presentations
This is a 3-day statistics course offered at Ohlone Community College's Biotechnology Center, in Newark, California (in Silicon Valley)

This 3-day course is scheduled for 7 hours per day, on Tuesday, Wednesday, Thursday, June 11, 12, 13, 2019.
For the 2019 course,  the cost per day is $100 per student.
Registration is now open, for each day's class separately, at the following webpages:

   Day 1 =
   Day 2 =
   Day 3 =

2019's informational brochures are now available (mouse-click on the desired day's link below):

Day 1                Day 2               Day 3

The main focus of the course is how to apply statistics in a practical way; other major foci are "valid statistical rationales for sample sizes" and "risk management".
The course is targeted at the medical device industry, but has been found very useful by those in the pharmaceutical and other biotech industries, as well as by
any industry that designs and/or makes products packaged in single units (as opposed to bulk solutions or bulk products like rolls of carpet).

Attendees may sign-up for any 1, 2, or 3 days of the workshop.                             

Day 1 topics:
•   Regulatory Requirements
•   Population vs. Sample
•   Parameter vs. Statistic
•   Probability
•   Law of Large Numbers
•   Distributions (in general)
•   Binomial Distribution
•   Normal Distribution
•   Central Limit Theorem
•   Standard Deviation and Standard Error
•   Linear Regression and Correlation Coefficients

Day 2 topics:
•   Regulatory Requirements
•   Confidence Intervals
•   Significance Tests
  •  Null Hypothesis
  •  t-Tests
  •  P-values
•   Power calculation (e.g., for t-Tests)
•   Confidence and Reliability (=% in-specification) Calculations (a.k.a., process capability calculations)
  •  Attribute ( pass / fail ) data
  •  Variables (measurement) data
      Normal vs. Non-normal data
      K-tables (for Normally-distributed data)
      Normality Tests, and How to Transformation Non-Normal data into Normality
  •  Statistical Justification for Sample Sizes and the use of only 3 Validation Lots

Day 3 topics:  
•   Regulatory Requirements
•   Reliability Plotting: confidence and reliability calculations (=% in-specification, a.k.a. process capability) for...
  •  Data that cannot be transformed to Normality
  •  Data with many replicate values
  •  Data from incomplete studies (i.e., time or equipment censored)
  •  Data comprising a mixture of distributions (bi-modal, tri-modal,...)
•   Metrology: Statistical Analysis of Measurement Variation (and how to use such information to set rational QC specifications)
•   QC Sampling Plans (and how to determine if they are "statistically valid", and what are better alternatives to using AQL plans).
•   Statistical Process Control (SPC)
  • Control charts (variables data, and count data)
  • Process Capability Indices

At the start of each day, the students are given a set of spreadsheets designed to help teach the topic
and to be used back at work to enforce and practice what's been learned.

At the end of each day, the students take a short open-book test, and then discuss the answers.
Click here
to go
back to
for public