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Quantitative Methods


  • Credit value: 15 credits at Level 4
  • Convenor: Grace Peng
  • Assessment: a two-hour multiple choice test (100%)

Module description

This module provides an understanding of core statistical principles and ideas.

You will learn how to summarise quantitative data effectively and appropriately, and use a statistical software package (SPSS) to input and analyse data, and interpret and report the results. You will also be able to select and use appropriate statistical methods for a range of different problems and data types.

Learning objectives

By the end of this module, you will be able to:

  • explain the difference between descriptive and inferential methods of data analysis
  • explain the meaning of categorical data and describe several graphical and non-graphical methods for summarising and presenting categorical data
  • explain the meaning of continuous data and describe a number of graphical and non-graphical methods for summarising and presenting continuous data
  • understand and interpret frequency distributions
  • distinguish between statistical samples and populations
  • explain what is meant by a confidence interval
  • explain the meaning of research hypotheses and significance testing, and describe the relationship between statistical significance, statistical power, sample size, and effect size
  • input data into SPSS and open SPSS data files
  • carry out exploratory data analysis using SPSS and interpret the results of this analysis
  • carry out some simple data transformations using SPSS
  • identify when to use and how to carry out using SPSS, how to report, and how to interpret the following: Pearson correlation, simple regression, multiple regression, hierarchical regression, logistic regression, exploratory factor analysis, chi-square test, independent and paired samples t-test, independent and repeated measures one-way ANOVA, and independent samples factorial ANOVA
  • explain the basic principles of path analysis and structural equation modelling.