School for Health, Unit Catalogue 2009/10 |
FH20107: Experimental design and communication skills |
 Credits:
| 12 |
| Level:
| Intermediate |
| Period: | Academic Year |
| Assessment:
| CW 100% |
| Supplementary Assessment: | Like-for-like reassessment (where allowed by programme regulations) |
| Requisites:
| Before taking this unit you must take FH10040 |
| Description: | Aims: To introduce an advanced level of data analysis skills and to develop each student's ability to effectively communicate scientific research findings. Learning Outcomes: On completion of this unit, students should be able to: * Perform a comprehensive literature review within a given area of study; * Compose a research proposal to address pertinent areas of investigation; * Identify the most appropriate research design for the selected area; * Understand the many factors influencing validity and reliability; * Conduct advanced statistical procedures in sport and exercise science both with and without the assistance of statistical software packages; * Interpret and present research outcomes both verbally and in text. Skills: Knowledge and Understanding - taught, facilitated and assessed Intellectual Skills - taught, facilitated and assessed Professional Practical Skills - taught, facilitated and assessed Written Communication - taught, facilitated and assessed Spoken Communication - taught, facilitated and assessed Numeracy - taught, facilitated and assessed Data acquisition, Handling and Analysis - taught, facilitated and assessed Information Technology - taught, facilitated and assessed Problem Solving - taught, facilitated and assessed Working Independently - taught, facilitated and assessed Working as part of a group - taught, facilitated and assessed. Content: Reviewing literature; presenting data graphically; presenting data orally; extension to basic inferential statistics; simple and factorial analysis of variance and covariance; normality and sphericity; statistical errors and multiple comparisons; statistical power and effect/sample size; methods of assessing reliability, validity and measurement error; multiple linear regression; in-depth analysis of research designs and their limitations. |