Multi-Vari Analysis

All of our training courses and programs are "hands-on", and are offered at the client's facility (on-site), anywhere in the world.

Course Description
This course provides an in-depth understanding of how and when to use multi-vari as a pre-experimentation and analytical tool to eliminate the major causes of variation in a process. It covers basic statistics tailored to understanding the more advanced analysis of multi-vari data. Emphasis is placed on statistical analysis (ANOVA) of multi-vari data in order to identify, quantify and reduce sources of process variation and improve the process. The course teaches the participants how to select the process variables to include in Multi-Vari, how to select a sampling scheme, how to implement it in production (chart), and more important, how to identify and quantify the major families of variation (positional, cyclical and temporal) in a process.

Course Description

This course provides an in-depth understanding of how and when to use multi-vari as a pre-experimentation and analytical tool to eliminate the major causes of variation in a process. It covers basic statistics tailored to understanding the more advanced analysis of multi-vari data. Emphasis is placed on statistical analysis (ANOVA) of multi-vari data in order to identify, quantify and reduce sources of process variation and improve the process.

The course teaches the participants how to select the process variables to include in Multi-Vari, how to select a sampling scheme, how to implement it in production (chart), and more important, how to identify and quantify the major families of variation (positional, cyclical and temporal) in a process.

Course Highlights	We Wrote the Book
Selection of Process Variables Construction of Multi-Vari Charts Descriptive Statistics, Mean, Variance, Sum of Squares Analysis of Variance Variance Decomposition Expected Mean Squares Interpretation of Multi-Vari Analysis Sources of Variation, Positional, Cyclical and Temporal Tier-Diagram for Multiple Variables Reducing Causes for Variation More... Duration: Typically 2 days.

We are Proud of Our "Hands-On" Training Approach
We take participants through lectures in which they learn the tools, methods, and concepts. Then, we help them apply the tools to their own processes. This is, by far, the most efficient way to learn the application of statistical methods.

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