Course Catalogue

Statistical Models (Bologna) STATS4070

  • Academic Session: 2026-27
  • School: School of Mathematics and Statistics
  • Credits: 16
  • Level: Level 4 (SCQF level 10)
  • Typically Offered: Semester 1
  • Available to Visiting Students: No
  • Collaborative Online International Learning: No
  • Curriculum For Life: No

Short Description

The course provides the basic theory of normal linear models and generalized linear models.

 

 

Timetable

Requirements of Entry

This course is only available to students on the Double Degree programme in Statistics with the University of Bologna.

Excluded Courses

Statistics 3L: Linear Models [STATS3016]

Linear Models 3 [STAST4015]
Regression Models (Level M) [STATS5025]

Statistics 3G: Generalised Linear Models [STATS3014]

Generalised Linear Models [STATS4043]

Generalised Linear Models (Level M) [STATS5019]

Co-requisites

-/-

Assessment

End-of-course examination, carried out in accordance with the assessment procedures and regulations of the University of Bologna.

Main Assessment In: December

Course Aims

This course aims 

■ to establish a solid understanding of (generalised) linear models and their practical relevance;

■ to train students in estimating and testing the significance of parameters in (generalised) linear regression models introduce students to the multivariate normal distribution; and

■ to expose students to variable selection procedures for these models.

Intended Learning Outcomes of Course

By the end of the course students will be able to:

■ formulate a normal linear model, estimate its parameters and test their significance;

■ use the variable selection procedures;

■ define a generalised linear model, by combining a random component with a linear predictor with a proper link function;

■ estimate and test the significance of the parameter of a generalised linear model; and

■ evaluate the goodness of fit of a model and detect violations of model assumptions.

 

Minimum Requirement for Award of Credits

No exceptions