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Unit information: Further Research Methods in Health Sciences in 2018/19

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Unit name Further Research Methods in Health Sciences
Unit code MVSFM0001
Credit points 20
Level of study M/7
Teaching block(s) Teaching Block 1 (weeks 1 - 12)
Unit director Dr. Andrew Wills
Open unit status Not open
Pre-requisites

None

Co-requisites

None

School/department Life Sciences Faculty Office
Faculty Faculty of Life Sciences

Description

This unit will build on the student's statistical literacy developed in Unit 1(Introduction to Research) alongside learning a range of laboratory techniques. The unit consists of self-directed home-based study materials (e-videos and quizzes), lectures, tutorials, and practicals that will prepare students for their MRes research projects. Teaching sessions will consolidate and expand their knowledge of statistical inference and experimental design, addressing topics such as estimation, inference, regression models, non-parametric methods and survival analysis. Students will also learn the basics of a statistical software package to manage data and carry out basic analyses. This will provide the basis for students to be able to design and interpret their own studies and analyses, and interpret and critically appraise the scientific literature. The statistical material will cover aspects important to both laboratory based experiments and epidemiological studies, including clinical trials. Laboratory-based practical classes will provide experience of laboratory skills and basic and advanced experimental techniques, including the methods used to study gene regulation, cell imaging techniques and tissue culture. Additional teaching will provide training in various aspects of laboratory safety, including the preparation of risk assessments

  • The aims of this unit are to:
  • (i) Provide students with a good understanding of the role that statistics and experimental design play in scientific research adn the concepts necessary to understand, interpret and draw conclusions from accepted study designs and statistical analyses.
  • (ii) Provide students with the skills needed to use a common statistical package for data management and statistical analyses competently.
  • (iii) Provide training and practical experience of basic and more advanced laboratory techniques.
  • (iv) Provide students with the core skills from which to undertake their research projects adn prepare students with the necessary foundation for more specialised courses appropriate to their area of study.

Intended learning outcomes

At the end of this unit the student should be able to:

  • (i) Demonstrate a good understanding fo the key concepts of statistical inference and be able to apply these concepts to their own research and to their comprehension of the medical and scientific literature.
  • (ii) Devise research questions, design effective studies/experiments and choose appropriate statistical methods for both laboratory and epidemiology-based research.
  • (iii) Accurately interpret and draw conclusions from a wide range of accepted statistical analyses.
  • (iv) Critically appraise the results from published laboratory and epidemiological studies
  • (v) Perform basic data management and statistical analyses using a statistical software package.
  • (vi) Work effectively within a research laboratory and demonstrate proficiency in basic laboratory skills, demonstrating organisation, decision-making and time management.
  • (vii) Demonstrate knowledge and understanding of th process of planning a piece of research.

Teaching details

This unit is taught through lectures, tutorials, laboratory-based practical sessions and home-based e-learning.

Assessment Details

Formatively assessed coursework that will include data analysis, interpretation and a critical appraisal exercise; use of eBiolabs; this will assess learning outcomes (i), (iii))-(v) & (vii). Exam to include data interpretation, critical appraisal and study design (70% of summative assessment); this will assess learning outcomes (i)-(v) & (vii). MCQ examination on laboratory techniques (30% of summative assessment); this will assess learning outcomes (vi)-(vii).

Reading and References

Diggle P, Chetwynd A. 2011. Statistics and Scientific Method: An introduction for students and researchers. OUP Motulsky H. 2014. Intuitive Biostatistics: A non-mathematical guide to statistical thinkin. OUP Kirkwood BR & Sterne JAC. 2003. Essential Medical Statistics. Second Edition. Blackwell Science

Selected relevant research papers

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