ADVANCED QUALITY ENGINEERING INC.

Basic Statistics: A Six Sigma Prerequisite

As more organizations embrace Six Sigma improvement methods, the need for training in basic statistics increases. The intent of this seminar is not to produce statisticians. It is to provide participants with a functional understanding of basic statistical methods. An understanding of these concepts and methods can enable individuals to make greater sense out of the information overload that occurs today. Unlike the traditional accounting models for data analysis, which generally require detail and accuracy, statistical models provide understanding of effects and phenomena based upon samples. Moreover, statistical methods can even predict outcomes.

The Ideal Learner

Participants who have a need for a basic foundation in statistical methods will find this seminar appropriate. The presentation is practical with a minimum of theory. Persons interested in pursuing additional training in other statistical techniques will find this seminar very helpful. It is a prerequisite for Six Sigma training. The instructor welcomes calls to discuss the fit of this seminar to participants needs.

Who should attend this seminar?

Manufacturing Engineers, Quality Engineers, and other production persons will find it very useful. Managers of these functions will also benefit greatly. Persons from service or administrative functions will receive exercises and applications tailored to their needs. 

This is a 8 hour course with a maximum class size of 24
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      What you will understand
  • How to use descriptive statistics
  • The nature of variation and how it is predictable
  • Measures of central tendency and dispersion
  • Concepts of probability
  • Types and use of sampling
  • Histograms and other charting techniques
  • The normal distribution and other statistical distributions
  • The use of confidence intervals

     On completion of this seminar you will be able to:
  • Provide a foundation in analytical methods necessary for today’s demanding environment
  • Enable better decision making through effective data analysis
  • Increase effectiveness of communication
  • Prepare for training in higher level statistical methods such as Six Sigma