Run by School of Human and Behavioural Sciences

20.000 Credits or 10.000 ECTS Credits

Semester 1

Organiser: Dr Ross Roberts

This module forms an essential element underpinning all the other modules within the School. It provides students with an understanding of the nature of science and the application of the scientific method to the study of sport, exercise and health, and fundamental skills in data management, analysis and interpretation. The module is split into two separate but inter-related halves.

Part A Research Methods & Design - examines the fundamental assumptions underlying both quantitative and qualitative research approaches, sampling, validity, reliability, and experimental design. Part B Computational Statistics - The purpose of this module is for students to understand research processes in sport, health, and exercise sciences covering computational statistics 1 Computational Skills 2 Computer (SPSS) Skills 3 Subject specific interpretational skills

The purpose of this module is for students to understand research processes in sport, health, and exercise sciences covering Computational Statistics and Research Methods. In Part A students will cover data management in SPSS, quantitative research methods, and qualitative research methods and analysis In Part B students will cover ANOVA and regression based analyses

good

good level of understanding presented

threshold

acceptable level of understanding presented

excellent

excellent level of understanding presented

1. Understand the principles underlying measurement in quantitative research

2. Demonstrate an understanding of the principles underlying variance testing (e.g., ANOVA) and regression (simple and multiple regression)

3. Interpret the main features of SPSS computer printout from ANOVA and regression analyses.

4. Appreciate how different philosophies about ways of knowing influence one’s approach to research design

5. Carry out basic procedures in the analysis of qualitative data

6. Understand the principles of experimental design

Type	Name	Description	Weight
EXAM	Part A Midterm Exam	this is a midterm exam covering the first half of Part A	20.00
EXAM	Part A Exam (JAN)	Students will complete an exam covering the latter half of Part A	30.00
VIVA	Part B viva	Students will complete a 20 minute viva where they will discuss their knowledge and demonstrate their understanding of particular statistical analyses	50.00

		Hours
Lecture	Part b 11 x 2 hour lectures This course will be taught through a combination of lectures, seminar, tutorials and workshops.	22
Practical classes and workshops	Part A 1 x 1 hour practical	1
Private study	Part A private study to include reading, formative assessments, updating portfolio/ notes, exam preparation	76
Practical classes and workshops	Part B 4 x 1 hour practical sessions	4
Private study	Part B - private study to include attendance at enhancement sessions, reading, updating portfolio/notes, exam preparation and assignment completion	76
Lecture	Part A 11 2 hour lectures This course will be taught through a combination of lectures, seminar, tutorials and workshops.	22

• Literacy - Proficiency in reading and writing through a variety of media
• Numeracy - Proficiency in using numbers at appropriate levels of accuracy
• Computer Literacy - Proficiency in using a varied range of computer software
• Self-Management - Able to work unsupervised in an efficient, punctual and structured manner. To examine the outcomes of tasks and events, and judge levels of quality and importance
• Exploring - Able to investigate, research and consider alternatives
• Information retrieval - Able to access different and multiple sources of information
• Inter-personal - Able to question, actively listen, examine given answers and interact sensitevely with others
• Critical analysis & Problem Solving - Able to deconstruct and analyse problems or complex situations. To find solutions to problems through analyses and exploration of all possibilities using appropriate methods, rescources and creativity.

• research and assess paradigms, theories, principles, concepts and factual information, and apply such skills in explaining and solving problems
• critically assess and evaluate data and evidence in the context of research methodologies and data sources
• describe, synthesise, interpret, analyse and evaluate information and data relevant to a professional or vocational context
• demonstrate evidence of competence in the scientific methods of enquiry, and interpretation and analysis of relevant data and statistical outputs.

Talis Reading list

http://readinglists.bangor.ac.uk/modules/jxh-3058.html

Compulsory in courses:

• C883: BSc Clinical Sports Science year 3 (BSC/CLSPS)
• C603: BSc Sports Science year 3 (BSC/SPSC)