Statistics and Probability in Six Sigma

Overview/Description
Six Sigma bases its analysis and findings on the facts and figures at hand. Statistical studies and probability are the key tools that Six Sigma teams use to measure and analyze issues that are identified in the early stages of Six Sigma projects. This course explores basic statistical concepts that apply to Six Sigma. It distinguishes between enumerative and analytical statistics and population and sample characteristics, and describes the Central Limit Theorem. It also examines basic probability concepts and looks at dependent, independent, and mutually exclusive events, and multiplication and addition rules. This course is aligned to the ASQ Certified Six Sigma Green Belt certification exam and is designed to assist learners as part of their exam preparation.

Target Audience
Candidates seeking Six Sigma Green Belt certification; quality professionals, engineers, production managers, and frontline supervisors; process owners and champions charged with the responsibility of improving quality and processes at the organizational or departmental level

Expected Duration (hours)
2.0

Lesson Objectives

Statistics and Probability in Six Sigma

classify examples of enumerative and analytical statistics

distinguish between examples of population parameters and sample statistics

define the statistical terms "population" and "sample"

identify key concepts of the Central Limit Theorem

calculate the probability of an event in a given scenario

match the terms associated with probability to their definitions

calculate the probability of an independent event in a given scenario

calculate the probability of a dependent event in a given scenario

calculate the probability of a mutually exclusive event in a given scenario

identify how to use the multiplication rule to calculate probabilities of events

identify how to use the addition rule to calculate probabilities of events