## Module and Programme Catalogue

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## MATH3715 Linear Models

### 15 creditsClass Size: 60

Module manager: Professor J.T. Kent
Email: j.t.kent@leeds.ac.uk

Taught: Semester 1 (Sep to Jan) View Timetable

Year running 2007/08

### Pre-requisite qualifications

MATH2715 or equivalent

### Pre-requisites

 MATH2715 Statistical Methods

### This module is mutually exclusive with

 MATH5715M Linear and Nonparametric Models

Module replaces

MATH3713, MATH3823, MATH5823M

This module is approved as an Elective

### Module summary

Regression techniques are key methods in statistics which relate a response variable to one or more predictor variables. Simple linear regression assumes a relationship like y = ax + b, where y is then observed with normally distributed errors. This model makes many assumptions, all of which can be relaxed. In this module, we study regression models which allow more complicated data sets to be analysed. Many of these models can be brought together in the framework of generalized linear models.

### Objectives

On completion of this module, students should be able to:

a) prove basic linear model theory using matrix algebra;
b) use a computer package to fit regression models and generalized linear models (including the use of link functions, deviance and overdispersion) to data, and interpret the models;
c) fit and interpret the special cases of log linear models and logistic regression;
d) use a statistical package with real data to fit these models to data and to write a report giving and interpreting the results.

### Syllabus

(a) Introduction to linear regression; multiple linear regression;
(b) estimation and hypothesis testing;
(c) residual analysis; influential observations;
(d) subset variable selection .
(e) Generalized linear model; probit model; logistic regression; log linear models.

### Teaching methods

Due to COVID-19, teaching and assessment activities are being kept under review - see module enrolment pages for information

 Delivery type Number Length hours Student hours Example Class 7 1.00 7.00 Laboratory 2 1.00 2.00 Lecture 26 1.00 26.00 Private study hours 115.00 Total Contact hours 35.00 Total hours (100hr per 10 credits) 150.00

Examples sheets

### Methods of assessment

Due to COVID-19, teaching and assessment activities are being kept under review - see module enrolment pages for information

Coursework
 Assessment type Notes % of formal assessment Report 15-30 pages 20.00 Total percentage (Assessment Coursework) 20.00

Normally resits will be assessed by the same methodology as the first attempt, unless otherwise stated

Exams
 Exam type Exam duration % of formal assessment Standard exam (closed essays, MCQs etc) 3 hr 00 mins 80.00 Total percentage (Assessment Exams) 80.00

Normally resits will be assessed by the same methodology as the first attempt, unless otherwise stated