Module code: PSYM153

Module Overview

The module introduces students to basic statistical theory and critical thinking, building throughout the year towards an intermediate level of understanding of statistical analysis and reporting. It aims to develop students¿ understanding of statistical methods and foster the skills needed to think critically about psychological research. Teaching involves a combination of theory lectures and practical workshops with real world research examples. Each week, lectures cover a specific statistics or critical thinking topic. This is followed by a workshop that typically focuses on applying and practicing the theoretical content of the preceding lecture. Together, lectures and workshops provide knowledge of statistical analysis and critical thinking from both a theoretical and practical perspective, resulting in a good introduction and grounding in statistical research methods. 

Module provider


Module Leader

ASKEW Chris (Psychology)

Number of Credits: 30

ECTS Credits: 15

Framework: FHEQ Level 7

Module cap (Maximum number of students): N/A

Overall student workload

Workshop Hours: 32

Independent Learning Hours: 157

Lecture Hours: 44

Tutorial Hours: 1

Guided Learning: 22

Captured Content: 44

Module Availability

Year long

Prerequisites / Co-requisites


Module content

The weekly lectures and workshops will cover theory and practice related to and including the following indicative topic areas:

  • Introduction to research methods

  • Hypothesis testing and research designs

  • Descriptive statistics & significance testing - z-scores and normal distribution

  • An introduction to statistical testing, including t-tests, correlation, regression, ANOVA, nonparametric tests, analysing categorical data

  • Identifying and evaluating critical arguments - Evaluating theory & evidence

  • Constructing critical arguments

Assessment pattern

Assessment type Unit of assessment Weighting
Coursework Data Analysis and Reporting Assignment 1 35
Coursework Critical Thinking Assignment 30
Coursework Data Analysis and Reporting Assignment 2 35

Alternative Assessment


Assessment Strategy

The summative assessment strategy is designed to provide students with the opportunity to demonstrate understanding of both critical thinking and quantitative data analysis

1. Data Analysis and Reporting 1: This assignment has been designed to assess competence in test selection in relation to data evaluation, use of jamovi, and writing results in the formal style used in psychology. These are critical skills for employability and improving digital capabilities.

2. Critical thinking coursework: This assignment has been designed to provide students with the opportunity to demonstrate their skill in constructing a sound argument about a psychological question based on a critical evaluation of research. These are essential skills in the workplace.

3. Data Analysis and Reporting 2: This assignment has been designed to assess competence in test selection in relation to data evaluation, use of jamovi, and writing results in the formal style used in psychology. These are critical skills for employability and improving digital capabilities.

Formative assessment and feedback

Weekly MSc statistics workshops consist of a worksheet and data sets to analyse. Students receive feedback on their progress via a feedback sheet of worked solutions. In addition, workshop tutors provide individualised verbal guidance and feedback during the sessions. In statistics lectures and as part of guided learning, students complete MCQ questions and receive immediate feedback to enable them to check their understanding of the module content.

The module contains a high level of discussion about analysing psychological research and using it to answer psychological questions. Through this, good critical thinking is modelled by the lecturer, practiced by the students and continual feedback is given about how their arguments in classroom discussion map onto the standards of critical thinking outlined in the lectures. The MSc tutorials further support this in a smaller group that supports interaction from all students.

Module aims

  • Enable students to correctly analyse experimental data using basic statistical procedures and understand the assumptions and limitations of these
  • Enable students to correctly interpret statistical results and understand the correct formats used to present data and results
  • Introduce students to the critical evaluation of psychological research
  • Enable students to develop sound arguments based on critical evaluation of psychological research

Learning outcomes

Attributes Developed
001 To understand hypothesis testing, and it's relation to statistical parameters such as the p-value, effect size, power and significance K
002 Be familiar with descriptions of data, categorisation of data and basic statistical terminology K
003 Understand basic research design, methods and the role statistical analysis has herein CK
004 Be able to calculate descriptive statistics, understand the limitations and assumptions of these, and how to report them most effectively CKPT
005 Demonstrate in workshops and coursework the ability to conceptually understand a range of parametric and nonparametric statistical analyses and their assumptions, run them in jamovi, and report the results in standard APA format CKPT
006 Demonstrate in workshops and coursework the ability to interpret results from a variety of basic statistical procedure CKT
007 Demonstrate critical evaluation of psychological research in tutorials and coursework CKPT
008 Demonstrate in the critical thinking coursework assignment the ability to construct sound arguments CKPT

Attributes Developed

C - Cognitive/analytical

K - Subject knowledge

T - Transferable skills

P - Professional/Practical skills

Methods of Teaching / Learning

Lectures cover statistical theory as well as how to use jamovi (data analysis software) to run the statistical analyses discussed in lectures.

Students then gain practice applying these techniques using jamovi in their workshops. This is to enable students to not only understand the theory behind statistical testing but also how to actually select and conduct the statistical tests using jamovi and interpret the results. The principles of critical thinking will also be presented in combination with practice applying these techniques. All these skills will also be essential for other modules; particularly the 'with Research Methods' modules and the final dissertation project.

Students are supported in interactive workshops and seminars by tutors who can answer questions and give formative feedback on work.

Students in statistics workshops receive written feedback sheets and can show their work to their workshop tutors to receive formative verbal feedback.

Readings are set each week from the core text book and students are expected to have done the reading before attending the workshop/seminar.

Students are taught in lectures and workshops to use jamovi software, an open-source statistical analysis software package. They are given the opportunity and support to develop their digital literacy and acquire transferable skills, including critical thinking and evaluation, creating and using data spreadsheets, and data analysis.

Thus the module contributes to building student independence, employability and digital capabilities.

Indicated Lecture Hours (which may also include seminars, tutorials, workshops and other contact time) are approximate and may include in-class tests where one or more of these are an assessment on the module. In-class tests are scheduled/organised separately to taught content and will be published on to student personal timetables, where they apply to taken modules, as soon as they are finalised by central administration. This will usually be after the initial publication of the teaching timetable for the relevant semester.

Reading list
Upon accessing the reading list, please search for the module using the module code: PSYM153

Other information

The School of Psychology is committed to developing graduates with strengths in Employability, Digital Capabilities, Global and Cultural Capabilities, Sustainability and Resourcefulness and Resilience. This module is designed to contribute to this in the following ways: Employability This module contributes to graduate employability by giving students the opportunity to develop and practice transferable skills that will be attractive to employers. These skills and capabilities include critical thinking, designing research, data analysis and interpretation, and using a statistical software package. Students will be familiar with descriptions of data, categorisation of data and basic statistical terminology, and will be able to demonstrate understanding and critical evaluation of basic research design, research methodology, and interpretation of findings. A freely available, open source statistical package is used on the module so that students can continue to use it for work after their studies. Digital capabilities Students have multiple opportunities to develop their digital capabilities, including using the university of Surrey Virtual Learning Environment (SurreyLearn) to access lecture materials, worksheets, data, videos and quizzes, as well as completing workshop worksheets and assignments using statistical analysis software. In particular, the weekly computer lab workshops offer an excellent opportunity to develop digital literacy by providing a supportive learning environment to develop and practice data analysis skills using jamovi statistical software. Resourcefulness and resilience The weekly workshops and assessments play an important role in developing students¿ resourcefulness and resilience. In statistics workshops/assessment, students are given example studies and data sets and are required to determine the most appropriate method of statistical analysis to address the research aims and hypotheses. In the critical thinking assessment, students are required to critically evaluate the research methods used in real-world examples of published research. The supported completion of weekly worksheets gives students better understanding and confidence with statistics, leading to increased independence and resilience.  

Programmes this module appears in

Programme Semester Classification Qualifying conditions
Psychology (Conversion) MSc(CORE) Year-long Core Each unit of assessment must be passed at 50% to pass the module

Please note that the information detailed within this record is accurate at the time of publishing and may be subject to change. This record contains information for the most up to date version of the programme / module for the 2025/6 academic year.