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BSc Optometry / Course details

Year of entry: 2020

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Course unit details:
Clinical Methodology 3

Unit code OPTO22062
Credit rating 0
Unit level Level 2
Teaching period(s) Semester 2
Offered by Optometry
Available as a free choice unit? No

Pre/co-requisites

Unit title Unit code Requirement type Description
OPTO12052 Pre-Requisite Compulsory
Clinical Methodology 2 OPTO22051 Pre-Requisite Compulsory

Aims

To provide experience of scientific calculations, data analysis, experimental design and the use of scientific software, with an emphasis on optometry and vision science requirements.

Learning outcomes

Students should:

  • Develop an understanding of the difference between parametric and non-parametric data and select appropriate statistical inference tests for each case.
  • Be able to select and apply appropriate statistical tests and extract parameter values from experimental data.
  • Be able to use appropriate software; modify images; search online patent libraries.
  • Be more familiar with data underlying the understanding of function.

Syllabus

This course is delivered through Blackboard, there are no Lectures.

 

Assessment methods

  • Parametric statistical tests (1 week) - 11%
  • Dealing with non-parametric data (1 week) - 11%
  • Non-parametric statistical tests (1 week) - 11%
  • Designing experiments and presenting results (1 week) - 11%
  • Manipulating images in Paint Shop Pro (1 week) - 11%
  • Patents and commercial exploitation (1 week) - 11%
  • Case study on Rhodopsin structure (1 week) - 11%
  • Case study using visual acuity data part 1 (1 week) - 11%
  • Case study using visual acuity data part 2 (1 week) - 11%

*Cumulative score on the assessed questions must exceed 70% for a pass. Passing this OPTO22062 course is required in order to pass the Personal and Professional Development module.

Feedback methods

Immediate feedback on submission of answers to practice quizzes and questions, including tips on questions that have been answered incorrectly. Score on submission of each assessment, along with a running total and average mark.

Recommended reading

  • Aitken MRF, Broadhurst RW & Hladky SB (2010) Mathematics for Biological Scientists, Garland Science
  • Ennos AR (2012) Statistical and Data Handling Skills in Biology (3rd Edition), Prentice Hall
  • Phoenix D (1997) Introductory Mathematics for the Life Sciences, CRC Press
  • Ennos R., Johnson M.L. (2018)  Statistical and Data Handling Skills in Biology (4th Edition), Pearson. 

Study hours

Independent study hours
Independent study 0

Teaching staff

Staff member Role
Stephen Prince Unit coordinator

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