University of Galway

Course Module Information

Course Modules

Semester 1 | Credits: 5

An introduction to the theory and application of regression models. Topics covered include the simple linear model, least-squares estimation, multiple linear regression, inference, model checking, model choice and variable selection, and the use of Minitab for practical applications.
(Language of instruction: English)

Learning Outcomes
  1. calculate and interpret correlations between variables and make inferences about relationships
  2. formulate a linear regression model, calculate estimated coefficients and make statistical inferences on the fitted model using both parameter estimates and the ANOVA table
  3. obtain fitted values and predictions at new data points, together with associated confidence intervals
  4. calculate regression diagnostics and use these to check model assumptions, including linearity, normality, constant variance, independence and the presence of outliers and influential points
  5. formulate a multiple regression model and specify this in matrix form
  6. derive least-squares estimates for
  7. Use Principal Components Analysis to reduce the dimensionality of a complex data set
Assessments
  • Written Assessment (70%)
  • Continuous Assessment (30%)
Teachers
Reading List
  1. "Applied linear statistical models" by Michael H Kutner
    ISBN: ISBN007238688.
The above information outlines module ST313: "Applied Regression Models" and is valid from 2019 onwards.
Note: Module offerings and details may be subject to change.