Module PSYC42415: Statistics for Psychology and the Behavioural Sciences

Department: Psychology

PSYC42415: Statistics for Psychology and the Behavioural Sciences

Prerequisites

• None

Corequisites

• None

Excluded Combination of Modules

• None

Aims

• To teach students a core set of statistical methods that are commonly used across psychology and the behavioural sciences
• To provide students with the capacity to confidently identify appropriate statistical techniques and analyse data using relevant software across a range of different types of research

Content

• Indicative content as follows:
• Data collection and validation
• Data management and organisation
• Exploring and presenting data
• Interpretation and reporting of descriptive statistics
• Statistical inference/ null hypothesis testing/ multiple testing correction/ power analysis
• Basic parametric (e.g., t-tests) and non-parametric techniques (e.g., chi-square, correlation)
• Analysis of Variance (ANOVA) (One way / Two-way, Repeated Measures, Mixed Models)
• Multivariate ANOVA (MANOVA)
• Analysis of Covariance (ANCOVA)
• Simple linear regression
• Multiple linear regression
• Dimension reduction

Learning Outcomes

• On completion of this module, students will acquire knowledge and understanding of:
• A range of common-used statistical tests in psychology and the behavioural sciences
• The importance of the role of statistics in any successful data analysis 
• The assumptions and limitations of the statistical techniques covered 
• The advantages and limitations of using different statistical software (e.g., SPSS, R, JASP)

• By the end of the module students should be able to:
• Use and apply a range of statistical techniques commonly used in psychology and the behavioural sciences
• Effectively use statistical applications software (e.g., SPSS, R)
• Analyse data accurately
• Interpret data appropriately
• Create reproducible analyses and reports

• Students will also develop some important key skills, suitable for underpinning study at this and subsequent levels, such as:
• Implement general IT and research skills
• Organsiation and datat management skills
• 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 teaching will usually 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 1-2 hours of practical activities in which students will undertake practical data analysis exercises using statistical software.
• The summative assessment will consist of one end-of-term assignment. The end-of-term assignment will require students to demonstrate their knowledge and understanding of statistics by independently conducting and reporting several statistical analyses and answering a series of theoretical questions.
• The formative assessment will consist of weekly practical exercises and pre-lecture questions. These will provide students with an opportunity to practice their statistical skills and will promote continuous engagement with the course material. These weekly assignments will be discussed during the weekly practical workshops where students can gain feedback on their progress

Teaching Methods and Learning Hours

Summative Assessment

Formative Assessment:

Formative student assessments (both written and oral) will be undertaken throughout the duration of the module. These will be assessed by the tutor to enable students to gauge their own individual rate of progress.

■ Attendance at all activities marked with this symbol will be monitored. Students who fail to attend these activities, or to complete the summative or formative assessment specified above, will be subject to the procedures defined in the University's General Regulation V, and may be required to leave the University