| Module Code | ST7002 |
| Module Name | Introduction to Multiple Linear Regression |
| ECTS Weighting[1] | 10 ECTS |
| Semester taught | Semester 2 |
| Module Coordinator/s | TBC |
Module Learning Outcomes
On successful completion of this module, students will be able to:
- To carry out an initial examination of the data
- To use a regression package (MINITAB) to apply multiple regression to simple data sets
- To interpret the results of the modelTo construct and exploit derived variables e.g. logs, products and indicator variables
- To understand the basics of logistic regression
Module Content
Multiple linear regression – and its many variants – is the most widely used tool in applied statistics. This course will build on simple linear regression, introduced in the Base Module. The aim is to become familiar with its use, to develop further experience and confidence in the use and role of statistical modelling. Specific topics addressed in this module include: Review of simple linear regression model: assumptions, model fitting, estimation of coefficients and their standard errors The multiple linear regression model and its analysis including: Confidence intervals and statistical significance tests on model parameters Issues in the interpretation of the multiple parameters Analysis of variance in regression: F-tests, r-squared Indicator variables and interaction terms Model validation: residuals, residual plots, normal plots, diagnostics Introduction to logistic regression
Teaching and learning Methods
The module will consist of 21 hours of lectures and 3 hours of labs
Assessment Details
| Assessment Component | Brief Description | Learning Outcomes Addressed | % of total | Week set | Week Due |
Reassessment Details
Examination (3 hours, 100%)
Contact Hours and Indicative Student Workload
| Contact Hours (scheduled hours per student over full module), broken down by: | 24 hours |
| Lecture | 21 hours |
| Laboratory | 3 hours |
| Tutorial or seminar | 0 hours |
| Other | 0 hours |
| Independent study (outside scheduled contact hours), broken down by: | 72 hours |
| Preparation for classes and review of material (including preparation for examination, if applicable | 0 hours |
| completion of assessments (including examination, if applicable) | 0 hours |
| Total Hours | 96 hours |
Recommended Reading List
Sheather, S. J. A Modern Approach to regression with R,, New York:, Springer 2009 Neter, J., Wasserman, W. & Kutner, M.H. Applied Linear Models , 2nd edition Boston, Irwin:1989 Kutner. M. H., Nachtsheim, C.J., Neter, J. & Li, W. Applied Linear Statistical Models, 5th, Boston: McGraw-Hill, 2005
Module Pre-requisites
Prerequisite modules: Base module ST7001
Other/alternative non-module prerequisites:
Module Co-requisites
None