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PU5054: ADVANCED QUANTITATIVE METHODS AND ANALYSIS FOR PSYCHOLOGY (2021-2022)

Last modified: 31 May 2022 13:05


Course Overview

This course teaches students in the field of health psychology how to conduct high quality quantitative research and how to think and operate within a professional, ethical framework. The structure of the course reflects the logical flow of the research process itself, moving week on week from the planning of research (generating and refining research questions, evaluating evidence, designing studies), through study conduct (ethical practice, quantitative methods, measurement issues, data handling, research governance) to the statistical analysis, interpretation, reporting and dissemination of research findings (to academic, policy, public, and media audiences).

Course Details

Study Type Postgraduate Level 5
Session First Sub Session Credit Points 15 credits (7.5 ECTS credits)
Campus Aberdeen Sustained Study No
Co-ordinators
  • Dr Julia Allan

What courses & programmes must have been taken before this course?

  • MSc Health Psychology

What other courses must be taken with this course?

None.

What courses cannot be taken with this course?

Are there a limited number of places available?

No

Course Description

This course teaches students in the field of health psychology how to conduct high quality quantitative research and how to think and operate within a professional, ethical framework. The structure of the course reflects the logical flow of the research process itself, moving week on week from the planning of research (generating and refining research questions, evaluating evidence, designing studies), through study conduct (ethical practice, quantitative methods, measurement issues, data handling, research governance) to the statistical analysis, interpretation, reporting and dissemination of research findings (to academic, policy, public, and media audiences).

 

Aims of the Course: This course aims to equip students with the skills and capabilities to use a range of quantitative research methods and analytic techniques within a professional, ethical framework.

 

At the end of the course, students will be able to;

 

  1. Identify and critically appraise the features of different research designs, data collection methods, analytic techniques and dissemination approaches
  2. Select appropriate study designs and analysis methods for different research questions and data types
  3. Generate novel material (e.g. research questions, hypotheses, questionnaire items, etc) that reflect understanding of key research principles
  4. Apply relevant ethical and professional practice frameworks to research and practice scenarios, identifying potential issues and generating strategies to minimise or avoid them
  5. Prepare and analyse complex data sets using advanced quantitative statistics, accurately interpreting and reporting the results
  6. Tailor research outputs so that they conform to published guidelines and are suitable for different audiences (e.g. public, stakeholder, academic)

 

The topics covered by the course

  • The research process (including critical appraisal, the scientific method, generating research questions)
  • Research design (including experimental, quasi-experimental, randomised, case-control, cohort, longitudinal, cross sectional, n-of-1, evidence synthesis)
  • Sources of bias in design, data collection and analysis; strategies to tackle this bias
  • Research ethics and governance, professional codes of practice
  • Questionnaire design, construction and psychometrics
  • Data preparation and exploration, dealing with awkward data (missing data, transformation, etc)
  • Sampling and sample sizes
  • Diary methods, ecological momentary assessment, n of 1
  • Working with existing data (secondary data, linked data, routine data etc)
  • Advanced quantitative analysis (ANOVA, multiple regression, logistic regression, multi-level modelling)
  • Research dissemination (academic, policy, public)
  • Reporting research in line with published standards, guidelines and recommendations

Contact Teaching Time

Information on contact teaching time is available from the course guide.

Teaching Breakdown

More Information about Week Numbers


Details, including assessments, may be subject to change until 31 August 2023 for 1st half-session courses and 22 December 2023 for 2nd half-session courses.

Summative Assessments

Class Test

Assessment Type Summative Weighting 40
Assessment Weeks 14 Feedback Weeks 16

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Learning Outcomes
Knowledge LevelThinking SkillOutcome
Sorry, we don't have this information available just now. Please check the course guide on MyAberdeen or with the Course Coordinator

Report: Individual

Assessment Type Summative Weighting 40
Assessment Weeks 18 Feedback Weeks 20

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Students will complete a data analysis workbook after running appropriate statistical analyses on randomly allocated datasets (from a selection of possible datasets). The workbook will include questions on various aspects of their own individual analyses (data preparation, assumption checking, variable creation, result reporting, result interpretation, etc).

Learning Outcomes
Knowledge LevelThinking SkillOutcome
Sorry, we don't have this information available just now. Please check the course guide on MyAberdeen or with the Course Coordinator

Report: Individual

Assessment Type Summative Weighting 20
Assessment Weeks 19 Feedback Weeks

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Learning Outcomes
Knowledge LevelThinking SkillOutcome
Sorry, we don't have this information available just now. Please check the course guide on MyAberdeen or with the Course Coordinator

Formative Assessment

There are no assessments for this course.

Course Learning Outcomes

Knowledge LevelThinking SkillOutcome
ReflectionEvaluateGenerate novel material (e.g. research questions, hypotheses, questionnaire items, etc) that reflect understanding of key research principles
FactualEvaluateSelect appropriate study designs and analysis methods for different research questions and data types
FactualAnalysePrepare and analyse complex data sets using advanced quantitative statistics, accurately interpreting and reporting the results
FactualAnalyseIdentify and critically appraise the features of different research designs, data collection methods, analytic techniques and dissemination approaches
ProceduralCreateTailor research outputs so that they conform to published guidelines and are suitable for different audiences (e.g. public, stakeholder, academic)
ProceduralEvaluateApply relevant ethical and professional practice frameworks to research and practice scenarios, identifying potential issues and generating strategies to minimise or avoid them

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