This complete Six Sigma Black Belt course will prepare you to perform the role of a Black Belt; covering what’s necessary to successfully achieve Black Belt certification and performance standards. It includes problem solving with Minitab.

**The Black Belt Six Sigma DMAIC course is broken into Week 1 and Week 2 and comprised of:**

- 791 slides and 20 data sets
- Slide are well explained
- Statistical analysis and tools explained with Minitab examples
- Slides are designed for novices, trainers and consultants

✪ 100% satisfaction guarantee

✪Instant download after purchase

✪Post query in case of any help

ASQ BB Question set with explained solution(85 questions) worth $ 8.99 **Absolutely Free**

**Reviews**

#### John Murphy

#### Cory Hicks

#### Benjamin Obi Tayo

#### Fluff Miller

Absolute value for money !

Excellent material. I would recommend this course material to all who are trying to learn Six Sigma tools.

Very comprehensive CSSBB course material and the best part is the Minitab explanations.

I really liked the DOE part, well explained with examples

**DEFINE**

Understanding Six Sigma

Six Sigma Fundamentals

Selecting Projects

Kano’s Model

Identify Project CTQ

Project Charter

SIPOC

**Summary: **Define Deliverables

**MEASURE**

Understand CTQ Characteristics

Define Performance Standards

Quality Function Deployment (QFD)

Process Mapping

Pareto Analysis

Data Collection plan

Sampling and Sample size determination

Confidence Interval

Central Limit Theorem

Six Sigma Statistics

Measurement System Analysis

**Summary: **Measure Deliverables

**ANALYZE**

Concept of Y and X’s

Defining Performance Objective

Process Capability

Sigma calculation

Distribution & Statistics

Histogram

Box Plot

Normality Testing

Identification of X’s

Fishbone

What is Hypothesis Testing

Type I and Type II error

**ANALYZE**

**Hypothesis Testing **

- 1 Sample t-test
- 2 Sample t-test
- Homogeneity of variance
- Paired t-test
- ANOVA
- Test for Proportions
- Chi Square

Scatter plot and Correlation

Regression

General Linear Model

**Summary: **Analyze Deliverables

**IMPROVE**

Characterization of X’s

Design of Experiment (DOE)

- Explained with example
- Identify factors
- Choose factor levels
- Select design
- Randomize runs
- Collect data
- Draw conclusions
- Full Factorial Experiments
- Confounding

Pugh Matrix

Pilot

FMEA

**Summary: **Improve Deliverables

**CONTROL**

Need for process control

Quality plan

Lean Concepts

Statistical Process Control (SPC)

**Summary: **Control Deliverables

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