PUBLIC PRESENTATIONS(workshops, classes, seminars, and webinars)to be given by John Zorich |

IN-PERSON 2-day PRESENTATIONS: |

company; for registration information, write to: JOHNZORICH@YAHOO.COM

Day 1 topics:

• Basic vocabulary

• Confidence Intervals

• Significance Tests

- Null Hypothesis
- t-Tests
- ANOVA
- P-values

• Confidence and Reliability Calculations

- Attribute ( pass / fail ) data
- Variables (measurement) data

- • K-tables (for Normally-distributed data)

• How to Transformation Non-Normal data into Normality

• MTTF and MTBF calculations and confidence limits

- 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,...)

• QC Sampling 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.

DESIGN VERIFICATION, PROCESS VALIDATION, & STATISTICAL PROCESS CONTROL

company; for registration information, write to: JOHNZORICH@YAHOO.COM

• Basic vocabulary & concepts

• How to interpret Linear Regression Correlation coefficients

• How to calculate confidence intervals (for proportions & for measurements)

• How to perform an interpret t-Tests: "significance", "p-values", "power" and sample-size considerations, and the concepts of "superiority" and "non-inferiority".

• How to understand the output of an ANOVA calculation

• Calculation of confidence and % in-specification (=reliability) for

o attribute data

o MTTF & MTBF (Mean time to Failure, and Mean time between Failure)

o normally-distributed variables data (including test for normality)

o non-normal data after transformation to normality

o extremely non-normal data that cannot be transformed to normality

• Process Variation

• What is Statistical Process Control ( SPC ) ?

• Basic Types of Control Charts and how to construct them: XbarR, XbarS, XmR, P, and U.

• Control Limits: Calculation & Re-calculation

• Out of Control: How to Detect It, & What to Do if Detect It?

• Sample Issues: Random, Sub-grouping, & Sample Size

• Capability Indices and how to calculation them

• Non-normal Data, and its impact on SPC.

• How to Initiate & Implement a Successful SPC Program

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.

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