SCIE603 – Quality Assurance and Statistics for Applied Science

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Module code
SCIE603
Module title
Quality Assurance and Statistics for Applied Science
Prescription
To enable students to understand organisational techniques for establishing, maintaining and improving quality and business sustainability and to implement and maintain a statistically based product sampling programme, interpret the results and make recommendations.
Programmes
  • SX1707
  • SX1709
NZQA Level
Level 6
NZQA Credits
15
Delivery method
  • Web-Supported
Learning hours
Directed hours
75
Self directed hours
75
Total learning hours
150
Resources required
Learning Outcomes
Apply quality assurance, quality management and quality control concepts to workflow and the business cycle.
Apply industry-specific quality standards and advanced approaches to product quality.
Interpret statistical data collected for quality assurance purposes.
Analyse data using professional statistical software.


Content
- - Quality concepts and terminology
- Quality management systems (including ISO9001 and derivatives, LEAN, six-sigma)
- Quality control procedures and techniques
- The provision of evidence and the role of statistical tools
- Industry-specific quality standards
- The role of audit and review
- Professional statistics software
- Sampling design
- Hypothesis testing
- Probability concepts and distibutions
- Data analysis using parametric and non-parametric ANOVA
- Data analysis using parametric and non-parametric regression and correlation
- Data display
- Control charting
- Proficiency test analysis and interpretation

- Control charting
- Proficiency test analysis and interpretation

- Hypothesis testing
- Probability concepts and distibutions
- Data analysis using parametric and non-parametric ANOVA
- Data analysis using parametric and non-parametric regression and correlation
- Data display
- Control charting
- Proficiency test analysis and interpretation

Teaching and Learning Strategy
Learning will be facilitated using a range of teaching and learning methods, which may include:
* Practical – laboratory; practical or workshop sessions and activities; demonstrations
* Theory – includes web-supported tutor facilitated/directed presentations; lectures and tutorials; group activities; peer presentations and review; group/individual research; online learning activities; case studies; guest speakers

Assessment Criteria
Assessment in this module is achievement-based. The portfolio is comprised of multiple assessment tasks. To pass this module all tasks must be submitted and an overall minimum pass mark of 50% is required.