# Six Sigma Probability and Statistical Distributions

Six Sigma Green Belt    |    Intermediate
• 16 videos | 58m 34s
• Includes Assessment
• CPE
Likes 141
By determining the probability that a certain event, or multiple events, will occur during your business process improvement project, you'll have a better chance of planning an effective process design. You also need to understand the characteristics of various statistical distributions, and their suitability for different types of data. This course covers different Lean Six Sigma tools and techniques for calculating probability in process improvement initiatives, including independent events, mutually exclusive events, multiplication rules, permutations, and combinations. You'll also explore different types of distribution such as normal, Poisson, binominal, chi square, student's T, and F distributions, and how they can be applied in Lean projects to ensure process control. This course is aligned with ASQ's 2015 Six Sigma Green Belt Body of Knowledge.

## WHAT YOU WILL LEARN

• distinguish between common probability terms use the formulas for calculating the probability of simple and mutually exclusive events calculate the probability of given events calculate probability using the addition rule calculate probability using the multiplication rule calculate a permutation calculate a combination distinguish between types of variables
• identify characteristics of normal distribution calculate the cumulative probability from the z-value recognize examples of using a binomial distribution effectively recognize examples of using Poisson distribution effectively recognize characteristics of chi-square distributions identify uses for Student's t-distributions identify characteristics of F-distributions

## IN THIS COURSE

• 1.
Six Sigma Probability and Statistical Distributions
• 2.
Introduction to Probability
• 3.
Simple and Mutually Exclusive Events
• 4.
Independent and Dependent Events
• 5.
• 6.
The Multiplication Rule
• 7.
Calculating Permutations
• 8.
Calculating Combinations
• 9.
Probability Distributions
• 10.
Normal Distribution
• 11.
Calculating Probabilities from Z-values
• 12.
Binomial Distributions
• 13.
Poisson Distributions
• 14.
Chi-Square Distributions
• 15.
Student's t-Distributions
• 16.
F-Distributions

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