Quantitative Methods

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

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.

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.