Run by School of Human and Behavioural Sciences

20.000 Credits or 10.000 ECTS Credits

This module builds upon the techniques for approaching research design and data analysis that you learned in Year 1. Specifically, it will cover ways of designing and analysing research with particular reference to experimental design, analysis of parametric and non-parametric data, and the use of Regression and Analysis of Variance (ANOVA), related techniques and associated follow-up tests. The aim of this module is to help students to learn some more advanced procedures of data analysis and to be able to use them for the analysis of their own research. Because this module focuses on advanced statistical techniques, students are expected to possess adequate knowledge of the concepts covered in Year 1 research method modules. This module will advance your skills and confidence when addressing research design and statistical analysis, and is essential in preparing you for your own research projects.

This module builds upon the techniques for quantitative and qualitative research methods and data analysis that you have learned so far in your degree. The module will cover concepts of Questionnaire design, Partial Correlation, Regression, Qualitative statistics, The module also cover one-way ANOVA before moving on to factorial ANOVA, ANCOVA and non-parametric statistics. This module includes an interactive session, where you will have the chance to practice running the different tests you have learnt during the lecture.

good

A good answer to the task brief with evidence of additional reading, and original interpretation. Good understanding of research design, quantitative and qualitative research analyses covered in the module. Mostly accurate research analyses and interpretation. Evidence of good SPSS skill. Clear communication, with few errors in presentation and formatting.

threshold

An adequate answer to the task brief, largely based on lecture material and basic readings. Basic understanding of research analyses covered in the module. Some errors in research analysis and interpretation. Some errors and weaknesses in terms of communication, presentation and formatting.

excellent

An excellent answer to the task brief with evidence of additional reading, and original interpretation and in-depth understanding. Comprehensive understanding of research design, quantitative and qualitative research analyses covered in the module. Accurate research analysis and interpretation. Evidence of excellent SPSS skill. Clear, accurate and excellent communication, presentation and formatting.

1. Apply knowledge of research methods and statistics by analyzing data (including choosing appropriate analyses based on study hypotheses), producing graphical representations of data, and interpreting results with respect to the hypotheses.

2. Produce a concise scientifically written research report that uses appropriate advanced research analysis.

3. Interpret the main features of SPSS outputs from a variety of parametric and non-parametric analyses.

4. Perform descriptive and inferential statistical analysis and graphical representations of data.

5. Understand the difference between quantitative and qualitative research methods for collecting and analysing data.

		Hours
Private study	Students are expected to devote 160 hours of guided independent study. Independent study includes individual research and reading time, peer discussion, and assessment preparation.	160
Workshop	Students will have workshops to further develop practical research statistics.	10
Lecture	Students will receive lectures that broadly explain research design and statistics. These lectures will also help students prepare for exam and coursework assessments, including the opportunity to receive feedback from peers and ask questions to staff.	30

• 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
• 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.
• Presentation - Able to clearly present information and explanations to an audience. Through the written or oral mode of communication accurately and concisely.
• Teamwork - Able to constructively cooperate with others on a common task, and/or be part of a day-to-day working team
• Argument - Able to put forward, debate and justify an opinion or a course of action, with an individual or in a wider group setting
• Self-awareness & Reflectivity - Having an awareness of your own strengths, weaknesses, aims and objectives. Able to regularly review, evaluate and reflect upon the performance of yourself and others

• 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
• plan, design, execute and communicate a sustained piece of independent intellectual work, which provides evidence of critical engagement with, and interpretation of, appropriate data
• demonstrate effective written and/or oral communication and presentation skills
• work effectively independently and with others
• take and demonstrate responsibility for their own learning and continuing personal and professional development
• demonstrate evidence of competence in the scientific methods of enquiry, and interpretation and analysis of relevant data and statistical outputs.
• develop transferable skills of relevance to careers outside of sport, health and exercise sciences.
• communicate succinctly at a level appropriate to different audiences.

Resource implications for students

Students are advised to bring laptops to lectures so they can practice using statistical analysis program SPSS. It is advised students try to download this software ahead of starting the course. SPSS is free for students to download from Bangor University IT services. https://www.bangor.ac.uk/itservices/software-students.php.en. Note. SPSS does not work on some tablets and Chromebooks.

Talis Reading list

http://readinglists.bangor.ac.uk/modules/jxh-2051.html

Reading list

Sample List

Dancey & Reidy (6th Edition) Statistics without maths for psychology Field (4th Edition) Discovering Statistics Using SPSS

Ntoumanis, N. (2003). A Step-by-Step Guide to SPSS for Sport and Exercise Studies: A Step-by-Step Guide for Students. Routledge.

Hayes, A. F. (2017). Introduction to mediation, moderation, and conditional process analysis: A regression-based approach. Guilford publications.

Field, A. (2013). Discovering statistics using IBM SPSS statistics. Sage.

Field, A., & Hole, G. (2002). How to design and report experiments. Sage.

Tabachnick, B. G., Fidell, L. S., & Ullman, J. B. (2007). Using multivariate statistics (Vol. 5, pp. 481-498). Boston, MA: Pearson.

Gratton, C., & Jones, I. (2014). Research methods for sports studies. Routledge.

Compulsory in courses:

• C616: BSc Sport and Exercise Science year 2 (BSC/SES)
• C63P: BSc Sport and Exercise Science with Placement Year year 2 (BSC/SESP)
• C617: BSc Sport Science, PE & Coaching year 2 (BSC/SSCPE)
• C64P: BSc Sport Science, PE and Coaching with Placement Year year 2 (BSC/SSCPEP)
• C618: BSc Sport Sci: Strength & Conditioning year 2 (BSC/SSSC)
• C65P: BSc Sport Science: Strength & Conditioning with Placement Yr year 2 (BSC/SSSCP)