Architecture|Building|Construction and Planning|Innovation and Enterprise|Technology Management

The ‘PropTech Introduction’ module will explore the various types of property technology that are transforming international property markets. The...

The ‘PropTech Introduction’ module will explore the various types of property technology that are transforming international property markets. The aim of the module will be to develop an understanding of the main types of PropTech to create an enterprise proposal. The module will provide a broad conceptual framework to support the development of your enterprise approach based on a three part classification scheme for these platform technologies – information, transaction, and management. You will use the ‘business model canvas’ as a means of developing an enterprise proposal as the assessment for this module.

Summary 

This module will provide insights into different aspects of vascular biology. It will cover the cellular processes that occur during vascular...

‘Computational Biology’ introduces the students to advanced statistics, applied to the biological sciences. It builds on first year modules and...

‘Computational Biology’ introduces the students to advanced statistics, applied to the biological sciences. It builds on first year modules and introduces more advanced linear and generalised linear models, as well as approaches to model building and comparison. It also covers applications of linear models to large-scale genomic data, programming, permutation-based tests, power analysis and multivariate statistics.

In addition to providing the theoretical background of the approaches covered, the module puts much emphasis on practical implementation. Lectures are accompanied by weekly practical sessions in which you will work through analyses in the statistical software R, the standard in much of biological computing.

The module is assessed via online quizzes and two homework assignments. The quizzes focus on theoretical knowledge and the use of R. The homework assignment provide you with the opportunity to independently analyse larger datasets, interpret the results and write up their methods and findings in publication format.

This module will provide you with analytical skills that are essential for research across disciplines of biology and other branches of science and professional activities.

Indicative lecture topics and learning objectives:

Basic programming in R
	Introduction to probability
	Regression and linear models
	Analysis of Variance
	Multiple Regression and model diagnostics
	Model comparison
	Logistic regression, Generalized Linear Models
	Statistical power and simulation
	Matrices