Advanced Statistics for Research

The details
Colchester Campus
Postgraduate: Level 7
Monday 13 January 2025
Friday 21 March 2025
06 November 2023


Requisites for this module



Key module for

MSC C80612 Research Methods in Psychology,
MPHDC80048 Psychology,
PHD C80048 Psychology,
MSCIC998 Psychology with Advanced Research Methods,
MSCICB98 Psychology with Advanced Research Methods (Including Placement Year),
MSCICB99 Psychology with Advanced Research Methods (Including Year Abroad)

Module description

This module provides a detailed overview of the most common statistical tests used by postgraduate and postdoctoral researchers in psychology.

The module will build upon Statistics I. The course will provide opportunities to specialize in advanced concepts and statistical techniques, including multi-level modelling and Bayesian analysis. The course will also provide experience of using R for data processing and visualisation.

Module aims

The aim of this module is:

  • To provide a detailed overview of some advanced statistical tests used by postgraduate and postdoctoral researchers in psychology.

Module learning outcomes

By the end of this module, students will be expected to have a solid conceptual understanding of and have confidence in using a number of advanced statistical techniques, including:

  • Carry out reproducible analysis by using computer code.

  • Data visualisation.

  • Statistics as linear modelling (e.g.,: multi-level, glm, etc).

  • Power analysis and data simulation.

  • Synthesize the above while carrying out data exploration

  • Module information

    Students will develop an understanding when to use what advanced statistical technique and have an awareness of how to address common problems encountered when using these procedures.

    Students will know how to interpret and report these techniques appropriately, and be aware of common errors in the interpretation of data.

    Students will attain considerable experience of using R to analyse data. They will develop sufficient statistical computing skills to independently analyse data at an advanced level.

    Learning and teaching methods

    This module will be delivered via:

    • One 2-hour lecture per week.
    • One 1-hour workshop per week.


    The above list is indicative of the essential reading for the course.
    The library makes provision for all reading list items, with digital provision where possible, and these resources are shared between students.
    Further reading can be obtained from this module's reading list.

    Assessment items, weightings and deadlines

    Coursework / exam Description Deadline Coursework weighting
    Coursework   Lab based open book test    50.0% 
    Coursework   Homework Assignment 1    12.5% 
    Coursework   Homework Assignment 2    12.5% 
    Coursework   Homework Assignment 3    12.5% 
    Coursework   Homework Assignment 4    12.5% 

    Additional coursework information

    Learning outcomes 1), 2), 3) and 4) will be assessed via the homework assignments, while 5 will be assessed in the open-book test.

    Exam format definitions

    • Remote, open book: Your exam will take place remotely via an online learning platform. You may refer to any physical or electronic materials during the exam.
    • In-person, open book: Your exam will take place on campus under invigilation. You may refer to any physical materials such as paper study notes or a textbook during the exam. Electronic devices may not be used in the exam.
    • In-person, open book (restricted): The exam will take place on campus under invigilation. You may refer only to specific physical materials such as a named textbook during the exam. Permitted materials will be specified by your department. Electronic devices may not be used in the exam.
    • In-person, closed book: The exam will take place on campus under invigilation. You may not refer to any physical materials or electronic devices during the exam. There may be times when a paper dictionary, for example, may be permitted in an otherwise closed book exam. Any exceptions will be specified by your department.

    Your department will provide further guidance before your exams.

    Overall assessment

    Coursework Exam
    100% 0%


    Coursework Exam
    100% 0%
    Module supervisor and teaching staff
    Dr Anna Hughes, email:
    Dr Anna Hughes;



    External examiner

    Dr Alexander Jones
    Middlesex University
    Senior lecturer
    Available via Moodle
    Of 30 hours, 0 (0%) hours available to students:
    30 hours not recorded due to service coverage or fault;
    0 hours not recorded due to opt-out by lecturer(s).


    Further information

    * Please note: due to differing publication schedules, items marked with an asterisk (*) base their information upon the previous academic year.

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