# Course details

Basic Probability and Statistical Distributions in Six Sigma

### Basic Probability and Statistical Distributions in Six Sigma

Overview/Description
Target Audience
Expected Duration
Lesson Objectives
Course Number

Overview/Description
To make accurate inferences about populations from sample data, you need to be able to determine the probability that an event or a combination of events will occur. You also need to be familiar with the characteristics of various statistical distributions, and their suitability for different types of data. In this course, you'll be introduced to the concept of probability. You'll learn how to calculate probability involving independent events, mutually exclusive events, multiplication rules, permutations, and combinations. You'll also look at different types of distributions, such as normal, Poisson, binomial, Chi-square, Student's t, and F-distributions. This course is aligned to the ASQ Body of Knowledge and is designed to assist Green Belt candidates toward achieving their certifications and becoming productive members of their Six Sigma project teams.

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)
1.7

Lesson Objectives

Basic Probability and Statistical Distributions in Six Sigma

• match the terms associated with probability to their definitions
• use the formulas for calculating the probability of simple and mutually exclusive events
• calculate the probability of given events
• calculate the probability of given events
• calculate probability using the addition rule
• calculate probability using the multiplication rule
• use addition and multiplication rules to calculate the probability of given events
• calculate a permutation
• calculate a combination
• use formulas to calculate permutations and combinations
• label examples of variables as continuous or discrete
• identify characteristics of normal distribution
• calculate probabilities based on normal distribution
• use formulas to calculate probability
• recognize examples of results that you could summarize using a binomial distribution
• recognize examples of results that you could summarize using a Poisson distribution
• distinguish between uses of binomial and Poisson distributions
• recognize characteristics of chi-square distributions
• identify uses for Student's t-distributions
• identify characteristics of F-distributions
• distinguish between Chi-square, Student's t, and F-distributions
• Course Number:
oper_26_a02_bs_enus