Bachelor of Science (BSc)

BSc Psychology

Academic psychology is a broad discipline that explores every aspect of behaviour, from the 'hidden' biology to everyday social phenomena.
  • Duration: 3 years (4 years with Study Abroad/Placement Year)
  • Year of entry: 2025
  • UCAS course code: C800 / Institution code: M20
  • Key features:
  • Study abroad
  • Industrial experience
  • Scholarships available
  • Accredited course

Full entry requirementsHow to apply

Course unit details:
Statistics and Data Analysis

Course unit fact file
Unit code PSYC21061
Credit rating 10
Unit level Level 5
Teaching period(s) Semester 1
Available as a free choice unit? No

Overview

This course unit builds upon the principles and techniques introduced in Introduction to Statistics for Psychological Sciences PSYC10100 for BSc Psychology students and the unit Introduction to Experimental Biology (BIOL10422) and Introduction to Laboratory Science (BIOL10401) for BSc Cognitive Neuroscience and Psychology students. Students who have not completed one of these Level 4 courses may need to do some independent study in preparation for the Level 5 course (please contact the unit lead for recommended resources).  

This course will cover statistical tests appropriate to a range of research designs which are commonly employed in psychological research. Focus will be placed on developing a theoretical (rather than mathematical) understanding of statistical procedures. Concepts common to these procedures will be emphasised to provide students with an appreciation of fundamental principles underpinning statistical analyses. Students will be guided in the use of statistical software (SPSS) for data analysis and will have regular opportunities to apply the procedures they have learnt to novel data. These data will always be contextualised within practical research scenarios and emphasis will  be placed on determining the appropriate analysis and providing a meaningful interpretation of results.  

This is a compulsory Year 2 unit for the BSc Psychology and BSc Cognitive Neuroscience and programmes. It provides a foundation for further study and independent project work in all units at level 6. 

Aims

  • Encourage a conceptual understanding of the logic underpinning a range of inferential statistical procedures commonly used in psychological research  
  • Instruct students in the use of SPSS for data analysis  
  • Equip students with statistical knowledge that will allow them to independently identify and conduct appropriate statistical analyses and interpret the results of these analyses  
  • Equip students with statistical knowledge that will allow them to independently evaluate the use of statistics in published research  

Teaching and learning methods

This unit will be taught via lectures and practical stats classes.  

It will be supported with an online textbook and links to relevant online resources 

Knowledge and understanding

  • Select appropriate statistical analyses based on research design and data properties  
  • Differentiate among research designs and statistical analyses, assessing their strengths and limitations
  • Explain fundamental principles of statistical theory  

Intellectual skills

  • Identify potential violations of key statistical assumptions and implement appropriate corrective actions  
  • Assess the suitability of analytical choices in published research and the validity of conclusions derived from these analyses
  • Interpret statistical results to draw meaningful conclusions within the context of a research hypothesis or question  
  • Identify and select appropriate variables and designs to operationalise research questions  
  • Evaluate the statistical methods chosen and the findings reported in empirical research 

Practical skills

  • Apply a range of quantitative analyses within psychological research contexts  
  • Demonstrate proficiency with specialist statistical software 

Transferable skills and personal qualities

  • Demonstrate effective data management and digital literacy skills essential to quantitative analysis
  • Employ numerical reasoning and analytical skills to interpret and present quantitative data
  • Communicate quantitative research results effectively through written and visual presentations 

Assessment methods

Assessment Task

Weighting within unit (if relevant)

Exam

70%

Qs 1 – 29 (40%) will include MCQ, matching, numerical answer

Q30 (30%) will be short answer (results ‘write-up’)

Quizzes

30% 
5 quizzes weighted 6% each

Feedback methods

Students will receive a grade and cohort level feedback

Recommended reading

Warren, P., Fisher, A. & Lewis, L. (2020). Statistics and Research Methods (5th Edition). Harlow: Pearson. 

Study hours

Scheduled activity hours
Practical classes & workshops 20
Seminars 8
Tutorials 7
Work based learning 22
Independent study hours
Independent study 43

Teaching staff

Staff member Role
Alison Fisher Unit coordinator

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