All researchers should have a grasp of both quantitative and qualitative data analysis methods as most projects will involve both to some degree. This chapter provides advice on the preparation of quantitative data and information about how to code this data. It then examines ways of analysing quantitative data using descriptive and inferential statistics. The statistics methods described include frequency distributions (tables, graphs or pie charts), measures of central tendency (mode, median, and mean or average) measures of variability (correlation coefficient and chi-square test). It also describes the most common parametric tests (t-test, F-test, analysis of variance (ANOVA), cluster analysis, factor analysis and regression analysis) and lists the non-parametric equivalents. Univariate and bivariate statistics are covered including and explanation of covariant and independent data relationships. The chapter closes with an update of the case studies followed by exercises, discussion questions and a debate topic.