How can research methods and statistics answer advanced research questions in psychology? As a postgraduate student, this module will deepen your ability to answer research questions such as how children improve in their skills year on year, whether a given training module improves the ability to correctly identify faces, or what factors predict prejudice in the workplace. You will learn about the logic of qualitative analysis and the many different forms it takes, and gain a firmer understanding of quantitative analysis, sampling, and statistical inference. In preparation for understanding and conducting research, you will learn advanced insights about correlational and experimental methods to understand relationships, causes and effects among variables. Building on this understanding, you will learn in-depth how simple correlations underlie understanding of multiple regression and its assumptions, and how regression in turn supports the general linear model, which is key to the other advanced topics taught in the module. The teaching will keep up-to-date with the latest advances in open science and transparent reporting of evidence. We will also use open source software to support practical lessons and assessments in data analysis, so that you can produce as well as understand the techniques being taught. Reporting your results through writing in APA style and appropriate data visualisation is an important skill that you will learn for a variety of analyses. There is also a special focus upon learning how to identify which analysis technique is right for any given statistical problem.
Lecture 24
Workshop 16
Independent Study 110
Assessment Preparation 50
Total Hours 200
The module is compulsory for the following courses
MSc Clinical Psychology
MSc Cognitive Psychology and Neuropsychology
MSc Developmental Psychology
MSc Forensic Psychology
MSc Organisational and Business Psychology
MSc Social Psychology
For Psychology Postgraduate Research degrees, individual students may be required to take this module on a non-credit basis as directed by their supervisory teams and depending on their prior level of statistical training.
Also available as an elective module.
Examination 2-hours (80%)
Weekly Computing exercises 8 x 30-minute assessments (20%)
*Both elements are pass compulsory and must be passed outright to achieve the learning outcomes of the module*
The University is committed to ensuring that core reading materials are in accessible electronic format in line with the Kent Inclusive Practices.
The most up to date reading list for each module can be found on the university's reading list pages.
On successfully completing the module, students will be able to:
1) Demonstrate conceptual understanding of the rationale and technique of different qualitative and quantitative approaches in research methodology;
2) Demonstrate systematic conceptual and practical understanding of the rationale and technique of advanced statistical inference approaches, using linear models and other techniques.
3) Advance autonomous problem-solving skills, learning how to use statistical software to manage and process data and carry out high-level descriptive and inferential analyses for a range of applications.
4) Understand, generate, and critically evaluate results of advanced statistical analyses and outputs of statistical software, as they would be reported in applied and basic psychological literature, and be able to communicate observations to specialist and non-specialist audiences.
5) Appreciate theoretical positions, practical applications, and controversies related to quantitative methods, qualitative methods, and inferential statistics, and their relevance to the student's field of study and social sciences more broadly;
6) Demonstrate the skills to analyse data and make sense of statistical materials; integrate numerical and non- numerical information; understand the limits and potentialities of arguments based on quantitative information
7) Deploy the skills to select and use the major analytic techniques employed by psychologists and to generate and test hypotheses on the basis of theoretical knowledge and gaps in relevant fields of psychology and their associated literatures.
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