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Data Analysis - MAN00106M

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  • Department: The York Management School
  • Module co-ordinator: Information currently unavailable
  • Credit value: 10 credits
  • Credit level: M
  • Academic year of delivery: 2022-23

Module summary

The module provides an introduction to quantitative and qualitative data analysis.

Module will run

Occurrence Teaching period
A Summer Term 2022-23

Module aims

The module provides an introduction to quantitative and qualitative data analysis.

 

In terms of quantitative data analysis, the module enables students to understand and apply the principles and techniques of statistical data analysis. It covers the statistical ideas/concepts and theoretical principles underpinning quantitative data analysis as well as the practical aspects and procedures of analysing quantitative data using SPSS (Statistical Package for the Social Sciences). It links the principles and processes of generating quantitative data (including probability sampling, normal distribution, operationalising variables, categories of data and levels/scales of measurement and questionnaire design) with the actual techniques of analysing and interpreting data and producing statistical results. The topics will cover descriptive and inferential statistics such as frequencies, measures of central tendency, graphs and charts, statistical tests, correlation and regression.

 

In terms of qualitative data analysis the module will enable students to understand and apply all elements of the qualitative data analysis process- assembly, reduction, display and verification.  This will involve handling data and organising and structuring it through data coding,  and being aware of different qualitative analysis methodologies such as content analysis, thematic  analysis, linguistic analysis and grounded theory (amongst other approaches).  It will also discuss the presentation of qualitative data analysis in written and visual form.  Students will also experience the use of CAQDAS (Computer assisted qualitative data analysis software) such as NVIVO.  Finally, students will also consider the ethical implications of qualitative data analysis. 

Module learning outcomes

Academic and graduate skills

  • At the successful completion of the module students will be able to:-
  • Apply the various statistical techniques and tools and appropriately apply them to different segments and types of quantitative and qualitative data
  • Use SPSS to manipulate available datasets demonstrating different levels of analysis from descriptive to multivariate analysis
  • Apply the various qualitative analysis techniques and tools appropriately to different types of qualitative data. 
  • Use NVIVO to code and analyse qualitative data. 

Module content

Subject content

  • Types of data/variables and levels of measurement
  • The normal distribution, hypothesis testing, correlation and regression
  • Qualitative data assembly, data reduction, data display and data verification.
  • Content analysis, thematic  analysis, linguistic analysis and grounded theory

The practical sessions will include:

  • Introduction to SPSS (e.g., data entering and manipulation, descriptive statistics, regressions)
  • Introduction to Data Coding and Nvivo

Assessment

Task Length % of module mark
Essay/coursework
Data Analysis Coursework		 N/A 100

Special assessment rules

None

Reassessment

Task Length % of module mark
Essay/coursework
Data Analysis Coursework		 N/A 100

Module feedback

A comprehensive module assessment report is released to students after the summer term exam board.  Individual written feedback is made available to students at the same time.

Indicative reading

Bazeley, P and Jackson, K. (2013) Qualitative Data Analysis with NVivo, Second Edition, Sage Publications.

Belk, R., Fischer, E., and Kozinets, R.V. (2013) Qualitative Consumer & Marketing Research, Sage publications.

Bryman, A and Bell, E – Business Research Methods – Oxford University Press – 2003

Bryman, A – Social Research Methods (3rd edition) – Oxford - 2008

Burnard, P., Gill, P., Stewart, K., Treasure, E and Chadwick, B. (2008) Analysing and presenting qualitative data, British Dental Journal, 204(8), 429-432.

Cassell, C (2015) Conducting Research Interviews, Sage Publications.

Field, A – Discovering Statistics Using SPSS (3rd edition) – Sage – 2009

Harding, J. (2013) Qualitative Data Analysis from Start to Finish, Sage Publications

Neuman, W. Laurence – Social Research Methods: Qualitative and Quantitative Approaches (6th edition) – Pearson - 2006

Bryman, A and Cramer, D – Quantitative Data Analysis with SPSS 14, 15 & 16 A Guide for Social Scientists – Routledge – 2009

Levine, DM,  Krehbiel, TC and Berenson, ML – Business Statistics A first course (5th edition) – Pearson – 2006

Oates, C and Alevizou, P. (2018) Conducting Focus Groups for Business and Management Students, Sage Publications.

Sweet, S and Grace-Martin, K – Data Analysis with SPSS – Pearson - 2008

Pallant, J – SPSS Survival Manual: A step by step guide to data analysis using SPSS - Open University Press – 2001

Yockey, R – SPSS Demystified: A Step-by-Step Guide to Successful Data Analysis – Pearson - 2007


The information on this page is indicative of the module that is currently on offer. The University is constantly exploring ways to enhance and improve its degree programmes and therefore reserves the right to make variations to the content and method of delivery of modules, and to discontinue modules, if such action is reasonably considered to be necessary by the University. Where appropriate, the University will notify and consult with affected students in advance about any changes that are required in line with the University's policy on the Approval of Modifications to Existing Taught Programmes of Study.