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Quantitative Methods & Data Analysis - MAN00029M

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  • Department: The York Management School
  • Module co-ordinator: Dr. Harry Venables
  • Credit value: 10 credits
  • Credit level: M
  • Academic year of delivery: 2020-21

Module will run

Occurrence Teaching cycle
A Summer Term 2020-21

Module aims

The module provides an introduction to quantitative data analysis. It aims to enable 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.

Module learning outcomes

At the successful completion of the module students will be able to:-

  • Understand the philosophy, methods, concepts and theoretical principles, which underpin quantitative data gathering and analysis
  • Learn the various statistical techniques and tools and appropriately apply them to different segments and types of quantitative data
  • Use SPSS to manipulate available datasets demonstrating different levels of analysis from descriptive to multivariate analysis


Task Length % of module mark
Quantitative Methods & Data Analysis - Coursework
N/A 100

Special assessment rules



Task Length % of module mark
Quantitative Methods & 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

Bryman, A. and Bell, E. (2003). Business Research Methods, Oxford University Press.
Bryman, A. (2008). Social Research Methods, (3rd edition), Oxford.
Field, A. (2009). Discovering Statistics Using SPSS, (3rd edition), Sage.
Neuman, W. and Laurence. (2006). Social Research Methods: Qualitative and Quantitative Approaches, (6th edition), Pearson.
Bryman, A. and Cramer, D. (2009). Quantitative Data Analysis with SPSS 14, 15 & 16 A Guide for Social Scientists, Routledge.
Levine, D. M., Krehbiel, T. C. and Berenson, M. L. (2006). Business Statistics A first course, (5th edition), Pearson.
Sweet, S. and Grace-Martin, K. (2008). Data Analysis with SPSS, Pearson.
Pallant, J. (2001). SPSS Survival Manual: A step by step guide to data analysis using SPSS, Open University Press.
Yockey, R. (2007). SPSS Demystified: A Step-by-Step Guide to Successful Data Analysis, Pearson.

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.