ÐÂÏã¸ÛÁùºÏ²Ê¿ª½±½á¹û

This module enables students to develop their understanding of the fundamental theories and techniques of statistics, to be able to rigorously collect process and analyse large (and sometimes imperfect) datasets, on subjects relevant to the construction industry. This module introduces key theories and concepts of data science and data analytics, which is of wide and growing relevance across the entire built environment sector, from design data and digital models (e.g. digital twins), to progression monitoring of on-site activities, and energy monitoring of built assets when in use. It equips them to handle data from digital models, commercial databases (e.g. economic and financial data) as well as other types of data. The module also provides basic training on an industry-standard tool for data visualisation (such as Tableau). This approach provides basic knowledge drawn from national datasets, company information, industry reports and textbooks. It extends students numeracy and analytical skills that will help them be able to understand project and business datasets, and the wider built environment context from which significant amounts of data are being generated. There is space to discuss and consider personal data and workforce data, such as protected characteristics.

Lectures, seminars and discussions in class, are informed by selected reading tasks.

Students are required to sit an open-book exam at the end of the module. The module leader provides formative feedback on a data visualisation exercise, and students gain experience of analysing and visualising example company datasets and economics reports – an important professional skills development opportunity.