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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 knowledgeOver TemplatesOver 40 Minitab Instruction Videos on advanced Six Sigma Black Belt Level topics are included in this Online Black Belt CourseStudent 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 _________________________________________________________________________________________________________________________________________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.

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