BA (Hons) Psychology and Mathematics Bachelor's degree at Strathclyde

Explores learning theory, developmental psychology, personality, biological psychology, and the scientific basis for psychology.

Covers sensation and perception, cognitive psychology, social psychology, abnormal psychology, and research methods.

Study of basic concepts and standard methods of mathematical notation and proof, polynomial equations and inequalities, sequences and series, functions, limits and continuity, differentiation and integration.

Fundamental concepts of calculus presented in more detail, extended to a larger class of functions by more sophisticated methods, including an introduction to complex numbers and variables, demonstrated in application to practical problems including solving basic first and second-order differential equations.

Introduction to vectors and matrices, along with the idea of mathematical modelling through their application to real-world problems.

Basic ideas and techniques of statistics while introducing essential study skills, allowing development and practice of personal and technical skills such as self study, teamwork, analysing data, writing reports and making presentations.

Introduction to a range of interesting applications and the mathematics behind them.

Understanding of higher mental functions through theoretical and experimental studies of normal human cognition and neuropsychological studies of how cognitive functions may be damaged as a result of brain lesions. Topics include disorders of the perceptual system, memory and attention, and the role of the frontal lobes in planning, motivation, emotion, and personality.

Social psychological theories and research providing insights into why people believe what they believe and why they behave the way they do. Topics include attribution theory, aggression, prosocial behaviour, group influence, norms, conformity, obedience, attitudes, and application of social psychological principles to health issues such as dietary behaviour, smoking/alcohol-use, and suicide.

Main features of measurement, research design, and statistical analysis in psychology. Presents fundamental concepts, issues, and debates in research methods, conceptual basis for inferential statistical testing, introduction to different inferential statistics, and brief introduction to qualitative research methods.

Basic ideas of linear algebra, such as matrices and determinants, vector spaces, bases, eigenvalues and eigenvectors. Various standard methods for solving ordinary differential equations and their relevance.

Basic ideas, techniques and results for calculus of two and three variables, along with differentiation and integration over curves, surfaces and volumes of both scalar and vector fields.

Rigorous treatment of convergence of sequences and infinite series of real numbers and of continuity, differentiability and integrability of functions of a real variable, illustrating the importance of these concepts in the analysis of problems arising in applications.

Basic concepts of probability theory and statistical inference to provide tools to appropriately analyse a given data set and effectively communicate results of such analysis.

Appreciation of basic concepts of force, momentum and energy, Newton's laws of motion, and application of these concepts to model physical systems, in particular the orbital motion of bodies.

Introduction to the R computing environment. Enables use of R to import data and perform statistical tests, understand the concept of an algorithm and what makes a good algorithm, and implement simple algorithms in R.

Broader, more advanced set of methodological and analytic skills. Skills essential for carrying out the year 4 dissertation and for being able to read and understand articles published in academic journals.

Scientific approach to conceptual and practical issues related to the study of individual differences, with specific reference to intelligence and personality. Opportunity to put knowledge into practice by designing own measurement instrument.

Core topics in cognitive psychology including perception and action, particularly how we perceive time and recognise faces; memory and learning, including models of episodic and working memory; language, including word production, sentence comprehension, and discourse processing; thinking, specifically problem solving, deductive reasoning and judgement and decision making.

Ways that children develop from infancy through to the end of adolescence. Key theories and exploration of whether children's development is continuous or stage-like. Core themes include infancy, theory of mind, executive function, language, and communication.

Basic principles of brain function and implications for understanding how behaviour is generated. Includes coverage of electrophysiology and psychopharmacology, neuroanatomy, research methods in neuroscience, and focused sections relating to the visual system and the motor system.

Current ideas and positions within social psychology. Four themes: attitudes and attitude change covering the Theory of Planned Behaviour and the Health Belief Model; identity with focus on social, personal and group identities; prejudice connecting attitudes and identities and covering social representations, stereotyping, prejudice and conflict; epistemology considering the theory of knowledge and how social psychological knowledge is produced.

Functions of a complex variable, concepts such as continuity, differentiability, analyticity, line integration, singular points. Important properties of such functions and applications such as conformal mappings and evaluation of real integrals using the Residue Theorem. Fourier and Laplace transform methods for solving linear ordinary differential equations and convolution type integral equations.

Basic algebraic structures with particular emphasis on those pertaining to finite dimensional linear spaces. Deepening understanding of linear mappings. Introduction to inner product spaces and bilinear forms.

Analytical methods for solving ordinary and partial differential equations to develop understanding along with technical skills in this area.

Generalisation of mechanics of single-particle systems to many-particle systems; central ideas of a continuum description of material behaviour and relevant constraints; basic principles governing three-dimensional motions of rigid bodies; ideas of continuum theory applied to static and inviscid fluids.

Review of concepts of probability distributions; approaches to parameter estimation, focusing on maximum likelihood estimation, bootstrap estimation, and properties of estimators; hypothesis testing procedures, including classical likelihood ratio tests and computer-based methods for testing parameter values, and goodness-of-fit tests.