Statistics and Methodology - SP801

Location Term Level Credits (ECTS) Current Convenor 2019-20
Canterbury
(version 2)
Autumn and Spring
View Timetable
7 40 (20) DR J Sabo

Pre-requisites

None

Restrictions

Not Available Wild.

2019-20

Overview

This module provides a postgraduate-level orientation to both basic and advanced contemporary statistical and methodological issues in psychology. The methodological issues considered include qualitative research methodologies; experimental, quasi-experimental, and correlational research designs in the laboratory and field; and the fundamental issues in psychological measurement including reliability and validity. The statistical techniques taught include univariate and multivariate descriptive and inferential statistics; basic and advanced topics in ANOVA and ANCOVA; linear and logistic multiple regression; some scaling methods; classical test theory, factor analysis; fundamentals of structural equation modelling (path analysis, confirmatory factor analysis, multiple-group analysis), and some item response theory.

Details

This module appears in:


Contact hours

Weekly three-hour lecture-workshops, weekly computing surgeries.

Method of assessment

Students complete two sets of examinations, each accounting for 50% of the final mark.

Indicative reading

The module reading list can be found online at http://resourcelists.kent.ac.uk/index.html

See the library reading list for this module (Canterbury)

Learning outcomes

The intended subject specific learning outcomes.
On successfully completing the module students will be able to:
8.1. Demonstrate a systemic understanding of the complex concepts and logic of statistical reasoning, using appropriate descriptive and inferential methods;
8.2. Comprehensively understand the fundamentals of scaling and methods used for measuring psychological variables;
8.3. Demonstrate a systemic understanding of the concepts of statistical model and model testing;
8.4. Use software SPSS to manage data, conduct descriptive analyses and test hypotheses; use software AMOS to specify and test structural equation models;
8.5. Interpret results of statistical analyses and outputs of statistical software; make inferences from the results in applied settings;
8.6. Systematically evaluate the appropriateness of statistical analysis methods to research design and data;
8.7. Effectively communicate results of statistical analyses orally and in writing.
8.8. Demonstrate a systemic understanding of how to apply qualitative, correlational and experimental research methods

The intended generic learning outcomes.
On successfully completing the module students will be able to:
9.1 Demonstrate an understanding of complex theoretical positions and controversies related to methodology;
9.2 Demonstrate an appreciation of the diverse applications of statistics and its relevance to students' fields of study and social sciences more broadly.

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