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2019/20 Taught Postgraduate Module Catalogue

DSUR5104M Statistical Methods

10 creditsClass Size: 30

Module manager: Jing Kang
Email: j.kang@leeds.ac.uk

Taught: Semester 1 (Sep to Jan) View Timetable

Year running 2019/20

Pre-requisite qualifications

Entry to the respective programmes listed above.

Co-requisites

DSUR5061M

Introduction to Research Methodology and Ethics

This module is not approved as an Elective

Module summary

This module introduces the concepts of statistical methodology and inference, particularly in quantitative research. Mixed methods will also be discussed, so that you will develop a more critical awareness in your reading of research papers. It will encourage you to think about which tests are appropriate for the analysis for different types of research design, so that when you come to design your own study, you will be better informed about these decisions.

Objectives

The objectives of this module are to:
- introduce statistical inference as the key tool for investigating diseases in a population;
- introduce a range of hypothesis tests used when studying health and disease in populations;
- develop understanding of when each test should be applied and the conditions required for each test to be valid, leading to choosing the most appropriate hypothesis test for a research question;
- develop understanding of how to soundly interpretation and present statistical hypothesis testing;
- enable the student to critically evaluate the use and interpretation of statistical tests in published literature;
- develop qualities that are appropriate to their future responsibilities to colleagues and society in general. As such, we aim to develop a professional attitude towards statistical inference.

Learning outcomes
Overall

By the end of this module participants should be able to:
- identify the appropriate statistical test to analyse data in a variety of situations;
- check the validity of the assumptions behind this test;
- perform this test using a statistical computer package;
- present their results appropriately;
- interpret the results of their analyses.

Transferable skills

By the end of this module the student should be able to:
- undertake on-line tasks, posting work and commenting on the work of others;
- reflect critically on their progress.

Syllabus

The module will cover the following subjects:
- Confidence intervals and t-tests;
- analysis of variance;
- chi-squared tests;
- McNemar's test;
- correlation;
- introducton to linear regression;
- Wilcoxon and Mann-Whitney tests;
- Kruskal-Wallis test and Spearman's correlation.

Teaching methods

Delivery type	Number	Length hours	Student hours
Lecture	4	1.00	4.00
Tutorial	4	1.50	6.00
Private study hours			90.00
Total Contact hours			10.00
Total hours (100hr per 10 credits)			100.00

Private study

Participants will be expected to finish assignment problems and to read relevant material in the recommended reading list provided.

Opportunities for Formative Feedback

This will be done in a number of ways:
- Student attendance and contribution to practicals.
- Module blog which encourage students to ask questions.

Methods of assessment

Coursework

Assessment type	Notes	% of formal assessment
Assignment	15	50.00
Assignment	15	50.00
Total percentage (Assessment Coursework)		100.00

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

Reading list

The reading list is available from the Library website

Last updated: 01/05/2019

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