Data Analysis

Data Analysis is the process of inspecting, cleaning, transforming, and modelling data with the goal of discovering useful information, suggesting conclusions, and confirming supporting theories. Data Analysis has multiple facets and approaches, encompassing diverse techniques under a variety of names, in different science, social science and business environments.

Data Analysis involves evaluating data using analytical and logical reasoning to examine each component of the data provided. Data Analysis is how researchers go from a mass of data to meaningful insights. There are many different data analysis methods, depending on the type of research, however data analysis has two prominent methods: qualitative research and quantitative research. Each method has its own associated techniques and practices.

Qualitative Research involves using data that approximates or characterises but does not measure the attributes, characteristics, properties, etc., of a thing or phenomenon. Quantitative Research involves using data that can be quantified, verified and measured, and is amenable to statistical manipulation. Quantitative data defines whereas qualitative data describes.  

A typical assessment, checking a student’s understanding of data analysis might be:

• Students should demonstrate knowledge and understanding of the basic concepts underlying the different procedures for data analysis covered in a module

• Given a research question and data, students should be able to undertake the appropriate type of analysis in an accurate, organised and clear manner

• Students should be able to interpret the results of the analysis and should demonstrate competence in critically reporting these results in relation to the research question