STAT3001

STAT3001: Statistical Modelling

Science and Engineering

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About this Unit

This unit will introduce students to different aspects of statistical modelling, estimation, and inference. Generalized linear modelling (GLM) extends Normal linear model theory to encompass distributions from the exponential family of distributions, including binomial (logistic regression) and Poisson distributions (loglinear models). Analysis of GLMs will also include formulation, estimation, model selection, diagnostic-checking, and evaluation of predictive ability. GLM will be extended to include extreme value theory and distributions. In time series analysis, the focus shifts to the analysis of data collected or observed sequentially in time. Students will be introduced to the modelling of different types of time series using autoregressive integrated moving average (ARIMA) models. Topics to be covered include exploratory data analysis, identification of ARIMA models, estimation, diagnostic checking, and forecasting.

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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

Lecture1 x 2 hours weekly
Tutorial1 x 1 hour weekly
Laboratory1 x 1 hour weekly

Prerequisites

Prerequisites group 1Select One

STAT2001v2Mathematical Statistics

Prerequisites group 2Select One

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