This module will be delivered via two lectures of Quantitative Methods, two lectures of Quality Control and one computer practical per week. Self-tests and tutorial sheets will be available through Blackboard to reinforce learning.
Module Aim:
The aim of this module is to develop the students' understanding of the statistical concepts and techniques used in science and their understanding of the role and benefits of quality systems in industry.
Learning Outcomes
On successful completion of this module the learner should be able to:
LO1
Calculate and interpret summary statistical measures and display data using statistical graphs and charts. Apply statistical tools to explore data.
LO2
Identify common probability distributions, in particular the normal distribution, and calculate associated
probabilities.
LO3
Describe fundamental quality concepts and identify quality improvement methodologies.
Pre-requisite learning
Module Recommendations
This is prior learning (or a practical skill) that is recommended before enrolment in this module.
No recommendations listed
Incompatible Modules
These are modules which have learning outcomes that are too similar to the learning outcomes of this module.
No incompatible modules listed
Co-requisite Modules
No Co-requisite modules listed
Requirements
This is prior learning (or a practical skill) that is mandatory before enrolment in this module is allowed.
No requirements listed
Module Content & Assessment
Indicative Content
Summary Statistics Data Organisation
Review of measures of central tendency and measures of dispersion. Data reduction, organisation and presentation. Population and sample, and data collection. Statistical critical thinking. Data cleaning.
Sampling and types of variables
Sampling techniques and introduction to probability distributions. Discrete and continuous random variables.
Fundamentals of Probability
Random variables and their associated probability distribution function. Examples of discrete
random variables. Overview of general discrete probability distributions, common discrete probability distributions, including the Binomial and Poisson probability distributions.
Normal Distribution
Continuous random variables, probability density functions. The Normal Distribution. Use of tables. Applications of the Normal Distribution in the Biological Sciences. Indicators of
normality and Normal Probability Plots.
Fundamental Quality Concepts
Definitions of Quality Control, Quality Assurance and Quality Management. Total Quality Management (TQM) and W Edwards Deming. Process model of quality and continous quality improvement.
Quality Standards
Definition of standards and standardization. Rationale, development and structure of standards. Standards supporting innovation. Accreditation and certification. GxPs. National and international standards bodies.
Economics of Quality
Definition and classification of quality costs, value of quality versus cost of quality. Problem solving tools including Pareto analysis, Vendor rating schemes, Flowcharting and Cause and effect analysis.
Assessment Breakdown
%
Continuous Assessment
70.00%
Practical
30.00%
Special Regulation
Students must achieve a minimum grade (35%) in both the CA and practical components of the course.
Continuous Assessment
Assessment Type
Assessment Description
Outcome addressed
% of total
Assessment Date
Examination
Quantitative Methods and Quality Control examinations and assessments
1,2,3
70.00
n/a
No Project
Practical
Assessment Type
Assessment Description
Outcome addressed
% of total
Assessment Date
Practical/Skills Evaluation
Computer practicals and assessments.
1
30.00
n/a
No End of Module Formal Examination
SETU Carlow Campus reserves the right to alter the nature and timings of assessment