This course will introduce PhD Researchers to the fundamental concepts in statistics using the R language and R Studio. R allows for basic and advanced statistical analysis which is why it is essential for the researcher. The course will involve an intuitive tutorial of basic descriptive, inferential and regression based statistics (parametric and non-parametric metrics, central limit theorem, normal distribution, measures of central tendency and variance [mean, variance, standard deviation, median, interquartile range], correlation coefficient, hypothesis testing, regression analysis). We will also look at histograms, density curves, scatter plots and box plots. There will be an exposure to programming structures and the R language nuances and syntax (Vectors, matrices, lists, data frames, factors, importing data and analyzing data using vectorised functions, concepts such as vectorisation, vectorised functions, recycling and sub-setting).
Shuai Zhang joined School of Computing and Mathematics and the Computer Science Research Institute in 2013 as an Associate Member. Shuai's research interests are in the areas of Intelligent Data Analysis for connected health applications.
Shuai graduated first class with a Bachelors degree in Computer Science after a four-year course with partial studentship at Heilongjiang University in Northeast China. She proceeded her study at University of Bradford and received an MPhil in Visual Arts Data Mining working on a novel voting algorithm for neuro-fuzzy classifier ensemble to identify similar Visual Arts objects. Shuai then successfully secured Vice-Chancellor's Research Scholarship at Ulster University to undertake her PhD study in Intelligent Data Analysis in School of Computing and Information Engineering. Her research focused on modelling semantically heterogeneous aggregate data in a distributed environment, which was then applied to learn inhabitants' behavioural patterns from unreliable low-level sensor data in smart environment to support assisted living. Continued with PhD research interest, Shuai has undertaken two research associate posts firstly in the CIPS project (Centre for Intelligent Point of Care Sensors) to model relationships between physiological change and Activities of Daily Living using wearable sensors potentially for everyday health monitoring. Before getting her first lecturer post in Ulster University, she joined MATCH project (Multidisciplinary Assessment of Technology Centre for Healthcare) to focus on modelling the benefits and costs associated with technologies for the delivery of Connected Health.
This session maps on to Domain A of the Vitae Framework: Knowledge and intellectual abilities which includes the sub-domain areas of: