Key Topics in Social Science: Measurement and Data

Learning Outcomes

Learning Outcomes

Having successfully completed this module you will be able to:

• Apply STATA programming commands to manipulate and analyse data; and interpret STATA output.
• Discuss the advantages and disadvantages of different data sources for empirical research on these issues.
• Appraise a variety of measures used to examine a variety of important social issues.
• Create your own empirical analyses on these social issues, applying your learning about relevant data, suitable measures and statistical software.

The range of subjects across the social sciences that are measured with quantitative data is very broad and the content of the module will need to be selective. The module will in particular cover topics relevant to core dimensions of living standards – for example, income inequality and poverty, education, work patterns, social mobility, crime, attitudinal data and subjective wellbeing. From year to year different topics will be covered, although at least one of the topics of income inequality and poverty will be taught each year. The content of the module will also vary with staff availability. A major feature of this module is the exposure to STATA.

Teaching and learning is through a mixture of a) lectures and b) computer workshops using the statistical software STATA. In the computer workshops students analyse data relating to the key topics discussed during the lectures.

Summative

This is how we’ll formally assess what you have learned in this module.

Referral

This is how we’ll assess you if you don’t meet the criteria to pass this module.

Repeat

An internal repeat is where you take all of your modules again, including any you passed. An external repeat is where you only re-take the modules you failed.