Statistics and Methodology - SP801

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Module delivery information

Location Term Level1 Credits (ECTS)2 Current Convenor3 2020 to 2021
Canterbury
(version 2)
Autumn and Spring 7 40 (20) PROF R Giner-Sorolla checkmark-circle

Overview

This module provides a postgraduate-level orientation to both basic and advanced contemporary statistical and methodological issues in psychology. The methodological issues you consider 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 you learn 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 the following module collections.

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.

Notes

  1. Credit level 7. Undergraduate or postgraduate masters level module.
  2. ECTS credits are recognised throughout the EU and allow you to transfer credit easily from one university to another.
  3. The named convenor is the convenor for the current academic session.
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