Department of Psychology, Unit Catalogue 2007/08 |
PS10088 Quantitative methods 1 |
| Credits: 6 |
| Level: Certificate |
| Semester: 2 |
| Assessment: CW 100% |
| Requisites: |
| While taking this unit you must take PS10087 |
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Aims: To develop students' competence in the design, conduct, analysis and reporting of experimental and practical work in psychology.
Learning Outcomes: * Be able to demonstrate the principles for analysing data from experiments * Be able to perform a range of statistical analyses appropriately and interpret statistical material. Skills: * To understand the scientific underpinnings of psychology as a discipline, its historical origins, development and limitations. (T/F) * Can demonstrate a systematic knowledge of a range of research paradigms, research methods and measurement techniques, including statistical analysis, and be aware of their limitations. (T/F A) * Can reason scientifically, understand the role of evidence and make critical judgements about arguments in psychology. (T/F) * Can adopt multiple perspectives and systematically analyse the relationships between them. (T/F) * Can pose, operationalise and critically evaluate research questions. * Can demonstrate substantial competence in research skills through practical activities. (T/F) * Can reason statistically and use a range of statistical methods with confidence. (T/F A) * Can comprehend and use numerical, statistical and other forms of data, particularly in the context of presenting and analysing complex data sets. (T/F A) * Is computer literate and is confident in using word processing, database and statistical software. (T/F A) Can solve problems by clarifying questions, considering alternative solutions and evaluating outcomes. (T/F A) * Can undertake self-directed study and project management in order to meet desired objectives. (T/F) * Is able to take charge of their own learning, and can reflect and evaluate personal strengths and weaknesses for the purposes of future learning. (T/F). Content: Students will have instruction in statistical methods including correlation, regression, ANOVA, and non-parametric statistics, and will apply these in the analysis of class data, and show their understanding of their use and interpretation. |