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Durham University

Faculty Handbook 2022-2023

Module Description

Please ensure you check the module availability box for each module outline, as not all modules will run each academic year.

Department: Psychology

PSYC3697: Statistical Modelling

Type Open Level 3 Credits 10 Availability Available in 2022/23 Module Cap 45 Location Durham

Prerequisites

  • • 10 credits from Level 2 Psychology

Corequisites

  • • Advanced Research Methods and Statistics

Excluded Combination of Modules

  • • None

Aims

  • To teach students a set of advanced statistical methods that are used across psychology, neuroscience and the behavioural sciences
  • To provide students with the capacity to confidently identify appropriate statistical techniques and analyse data using relevant software across a range of different types of research

Content

  • Indicative content as follows:
  • Modelling in R
  • Linear models
  • Logistic regression and general linear models
  • Multi-level modelling
  • Structural equation modelling
  • Multidimensional scaling and cluster analysis
  • Meta-analysis

Learning Outcomes

Subject-specific Knowledge:
  • On completion of this module, students will acquire knowledge and understanding of:
  • A range of advanced statistical tests used in psychology, neuroscience and the behavioural sciences
  • The assumptions and limitations of the statistical techniques covered
  • The advantages and limitations of using different statistical software (e.g., R, JASP)
Subject-specific Skills:
  • By the end of the module students should be able to:
  • Use and apply a range of advanced statistical techniques used in psychology, neuroscience and the behavioural sciences
  • Effectively use statistical applications software (e.g. R, JASP)
  • Analyse data accurately
  • Interpret data appropriately >
Key Skills:
  • Good written communication skills
  • Good IT skills in word processing
  • Ability to work independently in scholarship and research within broad guidelines

Modes of Teaching, Learning and Assessment and how these contribute to the learning outcomes of the module

  • Student understanding and practical ability to use the statistical tools will be facilitated by workshops supplemented with online material.
  • Students will watch online lectures asynchronously and on their own time study the theoretical material
  • The workshops will take place in a computer laboratory, where students will get experience in using the statistical tools
  • The weekly summative examination assesses students' acquired knowledge of theoretical principles through the weekly online test
  • The summative reports will assess students' ability to use the methods in practice, working on a small secondary data set
  • Formative tests will be given in class to prepare students for all summative tests

Teaching Methods and Learning Hours

Activity Number Frequency Duration Total/Hours
Workshops 5 Every 2 weeks 2 hours 10
Lecture (online) 10 1 per week 1 hour 10
Preparation and Reading 80
Total 100

Summative Assessment

Component: Summative Report Component Weighting: 90%
Element Length / duration Element Weighting Resit Opportunity
Statistics Report 50%
Statistics Report 50%
Component: In Class Tests Component Weighting: 10%
Element Length / duration Element Weighting Resit Opportunity
In Class Tests 8 x 5 Minutes 100%

Formative Assessment:

The formative assessment will be undertaken in class and feedback will be provided. Students will be set short-answer questions which might include being provided with secondary quantitative data sets to analyse and interpret.


Attendance at all activities marked with this symbol will be monitored. Students who fail to attend these activities, or to complete the summative or formative assessment specified above, will be subject to the procedures defined in the University's General Regulation V, and may be required to leave the University



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