STAT2004

STAT2004: Analytics for Observational Data

Science and Engineering

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About this Unit

Students will study the principles and practice of modelling and analysing observational data, with an emphasis on practical applications. The core concepts are probability modelling, prediction, and model checking and evaluation. Probability models for various kinds of data are introduced, including models for counts of events, categorical variables, waiting times, and other quantitative and categorical variables. The main focus is on analysing several or many variables, using statistical learning techniques such as correlation, discrimination, principal components and other dimension reduction methods, linear and generalised linear models, regularisation, feature and variable selection, and classification trees. Students taking this unit will be expected to be proficient in the precepts of reproducible research using languages such as R or Python.

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Unit Details

Credits25

Contact Hours4 Weekly

Result TypeGrade/Mark

AreaSchool of Electrical Engineering, Computing and Mathematical Sciences (EECMS) (1153)

Field of Education010103 Statistics

Handbook View Official Handbook Page →

Tuition Pattern

Computer Laboratory1 x 2 hours weekly
Lecture1 x 2 hours weekly

Prerequisites

PrerequisitesSelect One

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