Lean Six Sigma Black Belt Course
Lean Six Sigma Black Belt Course
As per Indeed, a job site's survey, Certified Six Sigma Black Belt salaries range between $100,000 - $200,000. Lean Six Sigma Black Belts command a premium in Job market. CSSBB & LSSBB deliver business results, so there are 75% more likely to be promoted that one without, but with similar domain experience.
This Lean Six Sigma Black Belt Training will help you succeed in accredited certification exam or process to become a certified Lean Six Sigma Black Belt because the BoK is based on Global Certification Bodies such as IASC and AQ curriculums.
Instructor is an Accredited Training Associate.
Every topic is application based. It starts with a business scenario and Six Sigma concepts are introduced subsequently.
There are 75+ Data Files & Practices Files for you to download.
You can follow the step-by-step instructions as you see in the lecture and mirror the instructor. It is a great way to master advanced statistical and analytics tools covered in Lean Six Sigma Black Belt body of knowledge
Over Templates
Over 40 Minitab Instruction Videos on advanced Six Sigma Black Belt Level topics are included in this Online Black Belt Course
Student Testimonials:
"I passed six sigma black belt certification exam. Black belt course and practice tests played pivotal role for cracking the test in one go. Thanks Nil !" - Sandeep J.
"This training material assisted me in the preparation of ASQ CSSBB exam. There are a lot of real-world examples included. Great Work! "- Temesgen E.
"Very thorough, will absolutely help a serious professional reach "create" level of proficiency - "Mastery" - Matthew M.
"The training was full of knowledge on whole plethora of Six Sigma application. The lessons were very informative in very simple languages. I recommend all to pursue this course under Udemy. Special Thanks to mentor Mr. Nilakantasrinivasan Janakiraman Sir". - Mofidur R.
CERTIFIED LEAN SIX SIGMA BLACK BELT Body of knowledge covered in this course are:
Black Belt leadership
Expectations from a Black Belt role in market
Leadership Qualities
Organizational Roadblocks & Change Management Techniques
Mentoring Skills
Basic Six Sigma Metrics
CTQ Tree, Big Y , CTX
Including DPU, DPMO, FTY, RTY, Cycle Time, Takt time
Sigma scores with XL, Z tables, Minitab
Target setting techniques
Role of Benchmarking
Business Process Management System
BPMS and its elements
Benefits of practicing BPMS (Process centricity and silos)
BPMS Application scenarios
BSC Vs Six Sigma
MSA
Performing Variable GRR using ANOVA/X-bar R method
Precision, P/T , P/TV, Cont %, No. of Distinct Categories
Crossed & Nested Designs
Procedure to conduct Continuous MSA
Performing Discrete GRR using agreement methods for binary and ordinal data
Agreement & Disagreement Scores for part, operator, standard
Kappa Scores Computation for ordinal data and criteria for acceptance of gage
Statistical Techniques
Probability Curve, Cumulative Probability, Inverse Cumulative Probability (Example and procedure), Shape, Scale and Location parameters
Types of Distributions ( Normal, Weibull, Exponential, Binomial, Poisson) & their interpretation and application
Identifying distributions from data
Central Limit Theorem - Origin, Standard Error, Relevance to Sampling
Example & Application of Central Limit Theorem
Sampling Distributions
Degrees of Freedom
t-distribution - Origin, relevance, pre-requisites, t-statistic computation
Chi-square distribution - Origin, relevance, pre-requisites, Chi-square statistic computation, Approximation to discrete data
F-distribution - Origin, relevance, pre-requisites, F-Statistic and areas of applications
Point & Interval estimates - Confidence and Predictive estimates for Sampling distributions
Application of Confidence Estimates in decision making
Sampling of Estimates
Continuous and Discrete Sample Size Computation for sampling of estimates
Impact of Margin of Error, standard deviation, confidence levels, proportion defective and population on sample size
Sample Size correction for finite population
Scenarios to optimize Sample Size such as destructive tests, time constraints
Advanced Graphical Methods
Depicting 1 or 2 variables (with example and procedure)
Dot Plot
Box Plot
Interval Plot
Stem-and-Leaf Plot
Time Series & Run Chart
Scatter Plot
Marginal Plot
Line Plots
Depicting 3 variables (with example and procedure)
Contour Plot
3D scatter Plot
3D Surface Plot
Depicting > 3 Variables (with example and procedure)
Matrix Plot
Multi Vary Chart
Inferential Statistics
Advanced Introduction to Hypothesis Tests
Significance and implications of 1 tail and 2 tail
Types of Risks - Alpha and Beta Risks
Significance & computation of test statistic, critical statistic, p-value
Sample Size for Hypothesis Tests
Sample Size computation for hypothesis tests
Power Curve
Scenarios to optimize Sample Size, Alpha, Beta, Delta such as destructive tests
Hypothesis Tests
1Z, 1t, 2t, Parried t Test - Pre-requisites, Components & interpretations
One and Two Sample Proportion
Chi-square Distribution
Ch-square Test for Significance & Good of Fit - Components & interpretations
ANOVA & GLM
ANOVA - Pre-requisites, Components & interpretations
Between and Within Variation, SS, MS, F statistic
2-way ANOVA - Pre-requisites, Interpretation of results
Balanced, unbalanced and Mixed factors models
GLM - Introduction, Pre-requisites, Components & Interpretations
Correlation & Regression
Linear Correlation - Theory and computation of r value
Non-linear Correlation - Spearman's Rho application and relevance
Partial Correlation - Computing the impact of two independent variables
Regression - Multi-linear Components & interpretations
Confidence and Prediction Bands, Residual Analysis, Building Prediction Models
Regression – Logistic(Logit) & Prediction - Components & interpretations with example
Dealing with Non-normal data
Identifying Non-normal data
Box Cox & Johnson Transformation
Process Capability
Process Capability for Normal data
Within Process Capability, Sub-grouping of data
Decision Tree for Type of Process Capability Study
Process Capability of Non-normal data - Weibull, Binomial, Poisson Process Capability and interpretation of results
Non Parametric Tests
Mann-Whitney
Kruskal-Wallis
Mood’s Median
Sample Sign
Sample Wilcoxon
Experimental Design
DOE terms, (independent and dependent variables, factors, and levels, response, treatment, error, etc.)
Design principles (power and sample size, balance, repetition, replication, order, efficiency, randomization, blocking, interaction, confounding, resolution, etc.)
Planning Experiments (Plan, organize and evaluate experiments by determining the objective, selecting factors, responses and measurement methods, choosing the appropriate design,
One-factor experiments (Design and conduct completely randomized, randomized block and Latin square designs and evaluate their results)
Two-level fractional factorial experiments (Design, analyze and interpret these types of experiments and describe how confounding affects their use)
Full factorial experiments (Design, conduct and analyze full factorial experiments)
Advanced Control Charts
X-S chart
CumSum Chart
EWMA Chart
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Note: We are not a representative of ASQ®, IASSC®
ASQ® is the registered trademark of the American Society for Quality.
IASSC® is the registered trademark of the International Association for Six Sigma Certification.
We are an independent training provider. We are neither currently associated nor affiliated with the above mentioned. The name and title of the certification exam mentioned in this course are the trademarks of the respective certification organization. The Fair Use of these terms are for describing the relevant exam and the body of knowledge associated.
A Comprehensive Certified Six Sigma Black Belt Training & Sure Shot Way to Become a Master of Six Sigma
Url: View Details
What you will learn
- Prepare for Lean Six Sigma Black Belt Certifications (CSSBB , LSSBB)
- Perform advanced data analysis using Minitab with 75+ datasets
- Downloadable material for future reference in each section covering Body of knowledge of accreditation bodies
Rating: 4.45
Level: Expert Level
Duration: 15.5 hours
Instructor: Nilakantasrinivasan Janakiraman
Courses By: 0-9 A B C D E F G H I J K L M N O P Q R S T U V W X Y Z
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