Overview

STATISTICAL ANALYSIS AND EXPERIMENTAL DESIGN: All students will follow a core program of lectures that will provide training in techniques of experimental design and analysis that are applicable to a wide variety of situations. In addition, students will have the option to consider specialised techniques of data analysis relevant to their chosen field of study; for example the use of R for graphing and statistical analysis. Students will undertake an online test to demonstrate their skills, analyse an advanced data set, and report on the contents of a scientific paper to the review development of hypotheses, experimental design, analysis of results, and conclusions drawn.

HEALTH AND SAFETY: The course will cover the duties of employees and employers under relevant Health and Safety and environmental legislation and consider strategies of waste reduction and management. Training will be given in identifying a wide range of biological, chemical and physical hazards and hierarchical strategies of risk control. Students will consider a number of relevant case studies to enhance their ability to carry out suitable and sufficient risk assessments. Work related upper limb disorders, associated with improper use of DSE, will be described and training given in how to carry out DSE assessments. On a practical level, this part of the module will help students to complete the risk assessments and other H&S and ethics requirements for their research projects.

Assessment Strategy

Threshold (D-) -Perform an adequate DSE assessment, be able to identify the most obvious hazards associated with scientific experiments and suggest some control measures. Be aware of relevant H&S and environmental legislation. Sound working knowledge of data handling and analysis techniques with the ability to apply the techniques to a range of straightforward situations. Superficial consideration of experimental design and logistics when undertaking scientific surveys, resulting in incomplete fulfilment of the brief. Sound but fairly limited data analysis, presentation and discussion of results.

Good (B) -Understand risks associated with the use of a poorly set up DSE workstation and perform an adequate DSE assessment. Be able to identify most of the major hazards associated with scientific experiments and suggest some control measures. Have a basic knowledge of relevant H&S and environmental legislation. In depth knowledge of data handling and analysis techniques with sufficient understanding to apply appropriate techniques to a wide range of datasets. Careful consideration of experimental design and logistics when undertaking scientific surveys of sampling, resulting in fulfilment of the majority of the brief. All data analysed and presented in a logical and clear manner with adequate discussion of results in relation to other relevant published literature.

Excellent (A) -Understand risks associated with the use of a poorly set up DSE workstation and perform an adequate DSE assessment. Be able to identify virtually all of the major hazards associated with scientific experiments and apply a hierarchical approach to risk control. Have a sound working knowledge of relevant H&S and environmental legislation. Thorough knowledge of data handling and analysis techniques with sufficient understanding to apply the most appropriate techniques to a wide range of complex datasets. Thorough consideration of experimental design and logistics when undertaking scientific surveys, resulting in complete fulfilment of the brief. All data analysed using the most appropriate techniques and presented in a concise and easy-to-follow manner with excellent and imaginative discussion of results in relation to other relevant published literature.

Learning Outcomes

• Assess the suitability of DSE workstations.

• Choose, apply and interpret appropriate techniques for analysing a variety of data sets.

• Effectively communicate the results of scientific surveys.

• Prepare suitable and sufficient risk assessments.

• Understand a variety of statistical tests and in what circumstances they could be appropriately used.

• Understand and communicate details about a given statistical test/approach, including the assumptions of the data, examples of scenarios where it may be applicable to use such a test, and comparisons with other similar experimental approaches.

• Understand duties under relevant Health and Safety and environmental legislation.

• Understand the link between hypotheses and appropriate experimental design and statistical approach.