Last updated 3/2021

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A Comprehensive Certified Six Sigma Black Belt Training & Sure Shot Way to Become a Master of Six Sigma

**What you'll 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

140 Quiz Questions as a mock to evaluate your Six Sigma knowledge

**Requirements**

Green Belt Certification & Green Belt Level working knowledge

The participant should have sufficient exposure to his/her domain or industry, It is advisable to have a minimum of 5-8 years of industry work experience

**Description**

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.

**Overview**

Section 1: Introduction

Lecture 1 Welcome

Lecture 2 Canopus BB course structure & curriculum & BB Certification Process I

Lecture 3 Softwares Needed

Section 2: BB Leadership

Lecture 4 Black Belt – Market expectations

Lecture 5 Black Belt Project - Do's & Don'ts

Lecture 6 Downloadable Takeaways

Section 3: Six Sigma Metrics

Lecture 7 Six Sigma Metrics Intro

Lecture 8 Six Sigma Metrics II

Lecture 9 Rolled Throughput Yield

Lecture 10 Baseline

Lecture 11 Target Setting

Lecture 12 Downloadable Takeaways

Section 4: VoC

Lecture 13 VoC Intro

Lecture 14 Gemba I

Lecture 15 Gemba II

Lecture 16 Gemba III

Lecture 17 Prioritizing Customer Needs using Kano Model (Recap Lesson)

Lecture 18 Conducting Kano Survey

Lecture 19 Downloadable Takeaways

Section 5: Business Process Management System

Lecture 20 BPMS Intro

Lecture 21 Organizational Silos

Lecture 22 Business Processes

Lecture 23 Big Y

Lecture 24 Types of Inputs

Lecture 25 Operational Definition

Lecture 26 CTQ Tree

Lecture 27 Business Process Management System

Lecture 28 Downloadable Takeaways

Section 6: Measurement System Analysis

Lecture 29 MSA Overview

Lecture 30 Elements of Measurement System

Lecture 31 Discrete Gage R&R

Lecture 32 Performing MSA Kappa Study

Lecture 33 MSA ANOVA

Lecture 34 Understanding MSA ANOVA Terms

Lecture 35 Performing MSA ANOVA 1

Lecture 36 Performing MSA ANOVA 2

Lecture 37 MSA Practice Files

Lecture 38 Downloadable Takeaways

Section 7: Statistical Techniques - Advanced

Lecture 39 Probability Distribution Refresher

Lecture 40 Standard Normal Variable

Lecture 41 Application of Probabilities

Lecture 42 Types of Distributions

Lecture 43 Distribution Parameters

Lecture 44 Process Lead Time Data

Lecture 45 Weibull Distribution

Lecture 46 Identifying Distributions

Lecture 47 Application of Weibull Distributions

Lecture 48 Exponential Distribution

Lecture 49 Binomial Distribution

Lecture 50 Binomial Application

Lecture 51 Poisson Distribution

Lecture 52 Poisson Distribution Application

Lecture 53 Normal Approximations

Lecture 54 Central Limit Theorem

Lecture 55 Application of Central Limit Theorem

Lecture 56 Statistical Techniques Practice Files

Lecture 57 Downloadable Takeaways

Section 8: Sampling Distribution

Lecture 58 Confidence intervals

Lecture 59 Confidence interval for means

Lecture 60 Degrees of freedom

Lecture 61 t-Distribution

Lecture 62 CI for t-Distribution

Lecture 63 Proportion of CI

Lecture 64 Chi-Square distribution

Lecture 65 F- Distribution

Lecture 66 Sampling Distribution Practice Files

Lecture 67 Downloadable Takeaways

Section 9: Estimate Sampling

Lecture 68 Estimate Sampling

Lecture 69 Rational Sub-Grouping

Lecture 70 Sample Size Computation Part 1

Lecture 71 Sample size computation for estimates for discrete data

Lecture 72 Sample Size Computation Part 2

Lecture 73 Sample size computation for estimates for Continuous data

Lecture 74 Sample size for finite population

Lecture 75 Estimate Sampling Practice Files

Lecture 76 Downloadable Takeaways

Section 10: Advanced Graphical Methods

Lecture 77 Graphical Methods Intro

Lecture 78 Dot Plots, Box Plots & Interval Plots

Lecture 79 Run Charts

Lecture 80 Time Series Plots

Lecture 81 Theory of R

Lecture 82 Non-linear correlation

Lecture 83 Marginal Plots

Lecture 84 3D Plots

Lecture 85 Multi Vary Charts

Lecture 86 Advanced Graphical Methods Practice Files

Lecture 87 Downloadable Takeaways

Section 11: Hypothesis Sampling

Lecture 88 Risks in hypothesis testing

Lecture 89 Sampling of hypothesis testing

Lecture 90 Hypothesis Sampling Practice Files

Lecture 91 Downloadable Takeaway

Section 12: Hypothesis Testing

Lecture 92 Hypothesis Testing

Lecture 93 Hypothesis testing in t-tests I

Lecture 94 Hypothesis testing in t-tests II

Lecture 95 Hypothesis testing in t-tests III

Lecture 96 ANOVA Fundamentals I

Lecture 97 ANOVA Fundamentals II

Lecture 98 Performing ANOVA I

Lecture 99 Performing ANOVA II

Lecture 100 Performing ANOVA III

Lecture 101 Type of Chi-square test

Lecture 102 Hypothesis testing using Chi-square tests

Lecture 103 Performing Chi-square tests I

Lecture 104 Performing Chi-square tests II

Lecture 105 Hypo Testing Proportion Test I

Lecture 106 Hypo Testing Proportion Test II

Lecture 107 Hypothesis Testing Practice Files

Lecture 108 Downloadable Takeaways

Section 13: Non Parametric Testing

Lecture 109 Non Parametric Intro

Lecture 110 One Sign & Wilcoxon Test

Lecture 111 Mann Whitney & Moods Median

Lecture 112 Non Parametric Testing Practice Files

Lecture 113 Downloadable Takeaways

Section 14: Correlation & Regression

Lecture 114 Line of Best Fit

Lecture 115 Regression in Minitab

Lecture 116 Fits & Residuals

Lecture 117 Partial Correlation

Lecture 118 Importance of Rsq

Lecture 119 Confidence Band and Prediction Band

Lecture 120 Multiple Linear Regression

Lecture 121 Multi-collinearity

Lecture 122 Best Subsets

Lecture 123 Logistic Regression Intro

Lecture 124 Performing Logistic Regression

Lecture 125 Predicting using Models

Lecture 126 Correlation & Regression Practice Files

Lecture 127 Downloadable Takeaways

Section 15: Design of Experiments

Lecture 128 Introduction to Experiments

Lecture 129 Phases of Experiments

Lecture 130 Basic DOE Terms

Lecture 131 Performing Full Factorial Experiment in Minitab

Lecture 132 Analyzing Full Factorial Results in Minitab - Part 1

Lecture 133 Analyzing Full Factorial Results in Minitab - Part 2

Lecture 134 Advanced DOE Terms

Lecture 135 Performing Fractional Factorial Experiments - Part 1

Lecture 136 Performing Fractional Factorial Experiments - Part II

Lecture 137 Analyzing Fractional Factorial Results in Minitab

Lecture 138 DOE Practice Files

Lecture 139 Downloadable Takeaway

Section 16: Process Capability

Lecture 140 Process Capability Intro

Lecture 141 Process Capability Decision Tree

Lecture 142 Performing Process Capability Analysis in Minitab I

Lecture 143 Performing Process Capability Analysis in Minitab II

Lecture 144 Performing Process Capability Analysis in Minitab III

Lecture 145 Interpreting Process Capability Analysis Results I

Lecture 146 Interpreting Process Capability Analysis Results II

Lecture 147 Data Transformation I

Lecture 148 Data Transformation II

Lecture 149 Data Transformation III

Lecture 150 Weibull Process Capability

Lecture 151 Binomial Process Capability

Lecture 152 Process Capability Practice Files

Lecture 153 Downloadable Takeaways

Section 17: Change Management

Lecture 154 Change Management & its importance

Lecture 155 Barriers to Change

Lecture 156 Accelerating Change

Lecture 157 Managing Change in BB Project

Lecture 158 Accountability for Improvement

Lecture 159 Change Management Strategies

Lecture 160 Downloadable Takeaways

Section 18: Statistical Process Control - Advanced

Lecture 161 Pre-Control Charts I

Lecture 162 Pre-Control Charts II

Lecture 163 Advanced Control Charts I

Lecture 164 Advanced Control Charts II

Lecture 165 Downloadable Takeaways

Lecture 166 Bonus Lecture: List of our other courses

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