Regression Modelling

Learning Outcomes

Learning Outcomes

Having successfully completed this module you will be able to:

• 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.
• 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 apply regression methods to typical data sets arising in official statistics.
• 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.

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

Teaching and learning methods

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..

Resources & Reading list

General Resources

Laboratory space and equipment required. Computing Lab in SPSS.

Textbooks

Agresti, A. (2013). An Introduction to Categorical Data Analysis. New York: Wiley.

Hosmer, W. H. , Lemeshow, S. and Sturdivant, T. (2013). Applied Logistic Regression (3rd edition). New York: Wiley.

Field, A. (2013 / 2017). Discovering Statistics using IBM SPSS Statistics. London: Sage.

Assessment strategy

There will be opportunities to evaluate your progress through formative assessment, with summative assessment based on one online assignment.

Summative

This is how we’ll formally assess what you have learned in this module.

Referral

This is how we’ll assess you if you don’t meet the criteria to pass this module.

Repeat Information

Repeat type: Internal & External