The student should be able to have a foundation in statistical analysis and be able to manipulate statistical data.

1. Summarise, describe data and identify the position of a data value in a dataset.
2. Determine the probability of an event using probability rules.
3. Calculate the probability for outcomes using discrete and continuous distributions.
4. Calculate confidence intervals for population mean, proportion and variance.
5. Perform hypothesis testing using parametric and nonparametric tests.
6. Make decisions and draw conclusions on the basis of statistical analysis.

The student should be able to advise a management team on Quality Management.

1. explain Quality Management Frameworks
2. explain approaches to team building and team dynamics
3. manage a quality improvement programme
4. communicate modern trends in Quality Management
5. appreciate the quality culture and dynamics in an organisation

Provides the student with a comprehensive understanding and knowledge of the use of statistical methods and techniques for monitoring and controlling processes.

1. Use and apply the basic problem solving techniques of quality to analyse data.
2. Apply qualitative tools for problems solving, prioritising problems and improving processes.
3. Develop, plot and analyse both variable and attribute Shewhart control charts.
4. Construct and use a EWMA chart
5. Apply short run and standardised control charts.
6. Conduct process and gauge capability analysis and develop the capability indices.
7. Conduct acceptance sampling by attribute and by variable data using ANSI/ASQC Z1.4 and ANSI/ASQC Z1.9 respectively.
8. Apply skip-lot, continuous and chain sampling procedures.

This module will provide the student with the tools necessary to plan, conduct and analyse experiments. The analytical interpretation of these results will allow the student to optimise products and processes.

1. Calculate correlation coefficient and conduct a test of significance.
2. Solve simple linear regression and curvilinear regression problems and make predictions.
3. Conduct one way and two-way ANOVA including the analysis of residuals.
4. Conduct and factorial experiments and analyse the resulting data.
5. Apply Taguchi methods involving calculation of loss function and signal-to-noise ratios.
6. Describe when and how to apply the appropriate experimental techniques and models
7. Use a statistical package to analyse and interpret experimental data.

The project aims to provide students with the opportunity to apply and integrate the skills and knowledge they have gained on the Quality modules they are studying. These modules are Statistics, SPC, Experimental Design and Quality Management.

The student should bring the learning from the modules covered in the course to identifying and leading six sigma projects within their organisation. Black Belts are the leaders in creating project teams, training and mentoring these teams and driving a culture of continuous process improvement within their organisation. A mentor will be assigned to each project.

The mentor will act as a guide in agreeing the relevance, and scope of the project, and monitor the progress on a regular basis. Updates will be sent to the mentor on an agreed basis.

Note: For external *ASQ Six Sigma Black Belt certification, ASQ requires two completed projects with signed affidavits or one completed project with signed affidavit and three years of work experience in one or more areas of the Six Sigma Body of Knowledge.

1. Identify a problem which needs to be addressed of importance to the organisation.
2. Lead the Six Sigma project meeting the goals of Time, Financial Savings and Requirements.
3. Utilise the Six Sigma DMAIC structured approach to manage the project. Apply appropriate Lean and Six sigma statistical tools in reducing process variation, optimising the process and realising financial savings.
4. Prepare a written report which outlines in detail the background to the project, a literature review outlining current knowledge in the project area, the methodology used to address the problem, discussion, conclusions and recommendations.
5. Present project results with Executive Summary, Conclusions and Recommendations and discuss the approach taken and results achieved.