37013 Understanding Data: Linear Regression Models for Interpretation and Prediction
2cp; 2hpw (lecture, online), 1.5hpw (PC labs, online)There are course requisites for this subject. See access conditions.
Anti-requisite(s): 60117 Understanding Data and Statistical Design
Recommended studies:
Students taking this subject must be familiar with basic statistical concepts such as random variables, sample and population statistics and t and F-tests.
Description
The motivation behind modelling data is to make judgements about the relationship between a response variable and predictor variables. This subject introduces linear regression, a statistical tool used to model continuous response variables and lays the foundation for further study in data modelling. The statistical tool is linear regression, a procedure that allows data to be modelled as lines, curves or surfaces of "best fit". The linear regression models considered involves combinations of continuous and categorical predictor variables. A major focus of the subject is analysis of the adequacy of the fit of the models to the underlying data, including procedures used to assess whether the modelling assumptions have been satisfied.
Detailed subject description.