Experimental Analysis

The details
Language and Linguistics
Colchester Campus
Postgraduate: Level 7
Monday 15 January 2024
Friday 22 March 2024
22 March 2022


Requisites for this module



Key module for

MRESQ14512 Analysing Language Use,
MRESQ10412 Experimental Linguistics,
MA Q15012 Psycholinguistics,
MPHDQ15048 Psycholinguistics,
PHD Q15048 Psycholinguistics

Module description

The module provides an introduction to Experimental Analysis. In lectures, students will be introduced to statistical techniques, whereas practical classes will offer students practice with implementing these techniques using freely-available R software. The module will cover basic principles such as sampling, distributions, and hypothesis testing, as well as how to select the appropriate statistics to analyse collected data. We will also discuss descriptive statistics and how best to report results in written work such as journal submissions and dissertations.

Students will be familiarised with how to test for relationships between variables (i.e., correlation and regression), and how to test for differences in behaviour between participants or groups (using, for instance, t-tests, ANOVAs, multiple regression, mixed effects modelling).

Module aims

This course aims to:
1. Prepare PG students for the analysis of original data
2. Provide preparation for reporting statistics in MA dissertations and published articles
3. Consolidate critical reading skills focused on understanding analysis methods reported in published articles
4. Promote the acquisition of ‘transferable skills’ (e.g., data manipulation and analysis, report writing, computer skills, etc.), which will be useful both inside and outside of academic contexts.

Module learning outcomes

On completion of the module, students will be able to:
1. Define key terminology related to experimental design and analysis
2. Summarise experimental studies in terms of hypotheses, design, variables, and analyses
3. Read and understand experimental and analytical methods reported in published articles
4. Use basic descriptive and inferential statistics to analyse data sets (using statistical analysis software such R)

Module information

Example syllabus:
1 – Introduction to statistics
2 – Sampling and distributions
3 – Correlation
4 – Linear regression
5 – Binomial regression
6 – T-tests
7 – ANOVAs
9 – Factorial ANOVAs
10 – Mixed effects models

Learning and teaching methods

This course consists of both asynchronous and lab-based elements: 1. 1-hour pre-recorded lectures are released on a weekly basis 2. 2-hour weekly in-person lab sessions Students are expected to attend labs regularly, and to actively contribute to discussions. Lectures must be watched in advance of lab sessions.


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   Assignment 1 (Moodle) - 29/01/2024    10% 
Coursework   Assignment 2 (Moodle) - 05/02/2024    10% 
Coursework   Assignment 3 (Moodle) - 12/02/2024    10% 
Coursework   Assignment 4 (Moodle) - 19/02/2024    10% 
Coursework   Assignment 5 (Moodle) - 26/02/2024    10% 
Coursework   Assignment 6 (Moodle) - 04/03/2024    10% 
Coursework   Assignment 7 (Moodle) - 11/03/2024    10% 
Coursework   Assignment 8 (Moodle) - 18/03/2024    10% 
Coursework   Assignment 9 (Moodle) - 25/03/2024    10% 
Coursework   Assignment 10 (Moodle) - 09/04/2024    10% 

Additional coursework information


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 Laurel Lawyer, email: l.lawyer@essex.ac.uk.
Laurel Lawyer
4.340, l.lawyer@essex.ac.uk



External examiner

Dr Ian Cunnings
University of Reading
Associate Professor in Psycholinguistics
Available via Moodle
Of 20 hours, 20 (100%) hours available to students:
0 hours not recorded due to service coverage or fault;
0 hours not recorded due to opt-out by lecturer(s), module, or event type.


Further information
Language and Linguistics

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