Predictive Analytics I (STAT30240)
Credits 5 Subject Statistics & Actuarial Science
Level 3 School Mathematics and Statistics
Semester   Information Semester One Module Coordinator Dr Michelle Carey

Students study: bivariate data (scatterplots and correlation); the simple regression model; least squares estimators and their properties; analysis of variation in the dependent variable; using the "extra sum of squares" to compare models; estimation of residual variance; inference from the linear model; regression through the origin; the multiple regression model; regression diagnostics (lack-of-fit and pure error) and residual plots; the one-way ANOVA model and assumptions; the regression model with dummy variables; parameter estimation using the least squares method; ANOVA tables and F ratio tests. Computer labs will be taken giving a full introduction to the R computer package, including fitting linear regression models and one-way ANOVA models using R.

Curricular information is subject to change