Applying Statistics in Lean Six Sigma

To put statistics into practice is to work with Lean Six Sigma. This course will teach you all the essential tools and techniques regarding intermediate statistics in Lean Six Sigma.
Course info
Level
Intermediate
Updated
Nov 20, 2020
Duration
1h 47m
Table of contents
Description
Course info
Level
Intermediate
Updated
Nov 20, 2020
Duration
1h 47m
Description

To turn data into knowledge is the real challenge for any Lean Six Sigma practitioner. In this course, Applying Statistics in Lean Six Sigma, you’ll learn how to run statistical analysis, tests, and transform them into business-friendly presentations. First, you’ll explore how to apply data to real-world situations. Next, you’ll discover how to apply hypotheses and sample tests. Finally, you’ll learn how to create advanced control charts. When you’re finished with this course, you’ll have the skills and knowledge needed to truly apply statistics into Lean Six Sigma.

About the author
About the author

Certified as a PMP, ITIL Expert, Scrum Master, Product Owner, Scrum Trainer and instructor accredited by Axelos.

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Section Introduction Transcripts
Section Introduction Transcripts

Course Overview
Hi, everyone. My name is Frederico Aranha, but please call me Fred. Welcome to my course, Applying Lean Six Sigma Statistics. I am an independent project management and governance consultant, as well as a certified Lean Six Sigma Black Belt. This course is your last step into understanding basic and intermediate is statistics applied to Lean Six Sigma. It is 100% based on the Lean Six Sigma Green Belt Training Manual from the Council for Six Sigma Certification, which we used with permission. Our main objective is to prepare you to run hypothesis tests and to understand and apply different types of statistical distribution. I'll also share with you good practices related to how to create business‑friendly presentations and communicate the results of your team's statistical analysis efforts. Some of the major topics that we will cover include a complete review on normal probability distributions and a presentation on several types of statistical distribution, such as exponential, lognormal, Weibull, Cauchy, logistic, Laplace, uniform, beta, gamma, triangular, binomial, geometric, and the Poisson distribution. Next, we're going to study hypothesis tests starting by a quick review on the subject. Then, I will explain null, alternative, and right hypothesis tests. I'll also teach you about proportion tests and hypothesis tests applied for discrete and continuous data. We'll study one and two‑sample t‑tests, the Mann‑Whitney test, and together, we'll reflect on how hypothesis tests can be better used within the DMAIC methodology. In the module, Presenting Statistics in Lean Six Sigma, I'll offer you insights on how to create business‑friendly presentations and share with you common challenges when presenting statistical analysis to overall stakeholders. I'll teach you storytelling techniques and how you can better use all tools we studied so far in the present learning path. At last, I'll introduce you to the Lean Six Sigma Green Belt certification exam syllabus and to sample exam questions. By the end of the course, you'll be ready to take the Lean Six Sigma Green Belt certification exam at the Council for Six Sigma Certification website. From here, try our Lean Six Sigma Black Belt learning path. I hope you'll join me on this journey and learn with me more about how to apply statistics in Lean Six Sigma, here at Pluralsight.