Course description
Regression Modelling
This module will provide an overview of statistical methods for linear and logistic regression.
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Outcome / Qualification etc.
Credits: 5 ECTS
Learning Outcomes
Having successfully completed this module you will be able to:
- On successful completion of this module you will be able to carry out an in-depth analysis of a dataset and undertake good statistical reporting.
- On successful completion of this module you will be able to apply regression methods to typical data sets arising in official statistics.
- On successful completion of this module you will understand and be able to apply the different techniques involved in fitting regression models.
- On successful completion of this module you will be able to use a statistical computing package to apply the different regression analysis techniques and understand and interpret the outputs.
Training Course Content
Linear regression covering;
- Basic (ordinary least squares) regression model
- Residual analysis
- Model building and selection for multiple regression model
- Assessing model fit
- Handling categorical variables, outliers, interactions, transformations
- Spline regression, polynomial regression, Weighted Least Squares
Introduction to logistic regression covering;
- Basic model
- Interpreting the parameters
- Assessing model fit
- Model building and selection
Course delivery details
Depending on feasibility, teaching may be delivered face to face intensively over a week, or online using a mixture of synchronous and asynchronous online methods, which may include lectures, discussion boards, workshop activities, exercises, and videos. A range of resources will also be provided for further self-directed study..
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