Teaching Responsibility
LJMU Schools involved in Delivery:
Psychology
Learning Methods
Seminar
Workshop
Module Offerings
7003POSPSY-JAN-CTY
Aims
To refresh and further develop existing knowledge and skills in qualitative and statistical analysis, interpretation, and reporting, thereby supporting empirical project work and critical evaluation of research in the field of positive psychology
Learning Outcomes
1.
Conduct, evaluate and demonstrate the appropriate use of qualitative analytic techniques in positive psychology research
2.
Conduct, evaluate and demonstrate the appropriate use of statistical analysis techniques in positive psychology research
3.
Communicate outcome of research analysis in a clear and concise manner appropriate to the discipline of psychology
Module Content
Outline Syllabus:Refresh knowledge of descriptive and inferential statistics, effect size, and probability based hypothesis testing.
Overview and training in quantitative computer packages (SPSS & Excel), introduction to qualitative software packages (e.g. NVivo)
Data management (validation of the data set, coding, data reduction, etc.)
Statistical analysis, for example, correlation, regression, mediation and moderation analysis, analysis of variance.
Qualitative analysis, for example, interpretative phenomenological analysis, narrative and discourse analysis, thematic analysis, grounded theory.
Module Overview:
This module enables you to develop knowledge and skills in qualitative and statistical analysis, interpretation and reporting - supporting empirical project work and critical evaluation of research in the field of positive psychology.
This module enables you to develop knowledge and skills in qualitative and statistical analysis, interpretation and reporting - supporting empirical project work and critical evaluation of research in the field of positive psychology.
Additional Information:Assessment is 100% Coursework split 50/50 between: 1) Qualitative analysis Report (2000 words); 2) Quantitative analysis Portfolio. The Quantitative Analysis Portfolio will have a final hand-in date by the end of module. Each component of the portfolio is connected to weekly topics and if each component is submitted by suggested milestone dates, students will receive feedback promptly so that they can use it for the next component in the Portfolio sequence. Portfolio assessments include demonstration of IT skills (e.g., SPSS, EXCEL, online calculators), short multiple-choice quizzes about statistical concepts, and writing of short results sections in APA style.