Module PSYC42315: Advanced Statistics for Psychology and the Behavioural Sciences

Department: Psychology

PSYC42315: Advanced Statistics for Psychology and the Behavioural Sciences

Prerequisites

• • PSYC42415 Statistics for Psychology and The Behavioural Sciences, OR SGIA49915 Quantitative Research Methods, OR alternative prior knowledge and understanding (i.e. firm understanding of how to explore data using appropriate descriptive statistics and graphs; confidence using R to undertake data management and statistical analyses, e.g. linear regression and visualisation; firm understanding of multiple linear regression through substantive analysis and the ability to implement, interpret and report, e.g. having passed the equivalent of one term of quantitative methods, up to and including linear regression; firm understanding of statistical inference, and the basis for this).

Corequisites

• None

Excluded Combination of Modules

• None

Aims

• To teach students a set of advanced statistical methods used across psychology and the behavioural sciences
• To develop students' capacity to confidently identify appropriate statistical techniques and analyse data using suitable statistical software across a range of research contexts

Content

• The module develops advanced approaches to statistical modelling and inference for psychology and the behavioural sciences. The specific sequence, emphasis, examples, datasets, readings and software used may vary from year to year to reflect developments in the field, staff expertise, student learning needs, and timetabling constraints. The following list is indicative and not exhaustive:
• Logistic and non-parametric (robust) regression
• Multi-level modelling
• Mediation, moderation and conditional process analysis
• Structural equation modelling
• Confirmatory factor analysis
• Multidimensional scaling and cluster analysis
• Meta-analysis

Learning Outcomes

• On completion of this module, students will be able to demonstrate knowledge and understanding of:
• A range of advanced statistical techniques used in psychology and the behavioural sciences
• Assumptions, limitations, and appropriate application of the techniques covered
• The advantages and limitations of using different statistical software packages that may be used to implement these techniques (e.g., SPSS, R, JASP)

• By the end of the module students should be able to:
• Select and apply appropriate advanced statistical techniques used to address research questions
• Use statistical software to conduct advanced analyses (using one or more packages as specified for module activities and assessment)
• Analyse data accurately and transparently
• Interpret and report results appropriately for a psychological/behavioural science audience.

• Students will also develop transferable skills, including the ability to::
• General IT and research skills relevant to advanced data analysis
• Manage their own time and resources
• Work to deadlines and within defined parameters

Modes of Teaching, Learning and Assessment and how these contribute to the learning outcomes of the module

• The weekly workshops will normally be taught in a computer laboratory and will typically include a 1-2 hour lecture which will outline the key statistical methods and concepts, how they can be used in psychology and the behavioural sciences, and their appropriate interpretation followed by practical activities in which students will undertake practical data analysis exercises using statistical software.
• The summative assessment consisting of statistical analyses and theory questions this will require students to demonstrate their knowledge and understanding of advanced statistics by carrying out analyses of pre-specified data-sets, writing up results and interpretation.
• Formative assessment provides students with an opportunity to perform, write up and obtain feedback on a series of analyses of pre-specified secondary data sets.

Teaching Methods and Learning Hours

Summative Assessment

Formative Assessment:

Formative assessment will be undertaken in class and feedback will be provided. Students will be set short-answer questions which might include being provided with data sets to analyse and interpret. The questions set for formative assessment will follow a similar format as the examination and is designed to familiarise students with the requirements and expectations.

■ Students who do not attend monitored activities shown under Teaching Methods and Learning Hours, or who fail to complete the summative or formative assessment(s) specified above, may be subject to the Academic Progress procedures defined in the University's General Regulation V, and may be required to leave the University.