This module will focus on key psychoanalytic theories on infancy and the caregiver-child relationship. It will encourage critical thinking on different...

Psychoanalytic Theories of Caregiver-Child Relationship (PSYC0281)

This module will focus on key psychoanalytic theories on infancy and the caregiver-child relationship. It will encourage critical thinking on different psychoanalytic perspectives by considering how the infant is portrayed in each theory and the emphasis given to the environment. Lectures will focus on particular theoreticians (Freud, Anna Freud, Klein, Winnicott, Bion, and others) and introduce their key ideas, papers and/or case studies about infancy. Lectures will also explore socio-cultural influences on these ideas, how these ideas were received at the time, and how they are used now. This module will introduce students to psychoanalytic concepts including the unconscious, drives, instincts, anxiety, ambivalence, defences, Oedipus, mourning and separation, phantasy, the inner world, the development of symbolic thinking, holding, transitional phenomena, container/contained, ‘ghosts in the nursery’ and about cultural complexity relating to theorizing about human development, parenting, the family and other relationships. This module will also allow students to compare theoretical ideas about babies, parenting and infantile states of mind with their own parent-infant observational experience.



The module will lay the theoretical foundations for the module ‘Applied Psychoanalytic Concepts’ module.

This course provides an introduction to statistics for analysing the results of psychological experiments and observational studies. The course covers...

Fundamental Statistics: Statistical and Causal Reasoning (PSYC0223)

This course provides an introduction to statistics for analysing the results of psychological experiments and observational studies. The course covers different types of data and how to describe them, the principles underlying null hypothesis significance testing, and common tests and analyses, including ANOVA, correlation, regression and the general linear model. The course will focus on how to decide on the suitable analysis for a given problem, and how to evaluate the appropriateness of a statistical model and its underlying assumptions. Emphasis is placed on a conceptual understanding of statistical methods, and in most cases definition rather than computational formula are presented. Practical experience in applying the methods will be developed through exercises in Microsoft Excel and with the statistics package SPSS.