Accessibility statement

Introduction to Regression Analysis - HEA00093M

« Back to module search

• Department: Health Sciences
• Module co-ordinator: Dr. Mona Kanaan
• Credit value: 10 credits
• Credit level: M
• Academic year of delivery: 2019-20

• None

• None

Module will run

Occurrence Teaching cycle
B Spring Term 2019-20

Module aims

To provide understanding and skills in using linear and logistic regression and non-parametric statistics. To be able to define commonly used terms in regression analysis and non-parametric statistics. To evaluate the use of statistical analysis in published research.

Module learning outcomes

Knowledge and understanding of the subject area:

• Demonstrate understanding of the principles underlying inferential statistics with an emphasis on linear and logistic regression and non-parametric statistics.

Cognitive and intellectual skills:

• Critically appraise results of research.
• Interpret the results of research.

Subject-specific skills:

• Be able to describe data and carry out linear and logistic regression and non-parametric statistics.
• Be able to critically appraise reports of research which have used a range of methods including linear and logistic regression.

Key transferable skills:

• Be able to use SPSS for analysing data.

Module content

The module assumes basic knowledge of descriptive statistics and basic inferential statistics.

Module content:

Estimation

• Standard error and confidence intervals

Linear Regression Analysis

• Introduction to Simple Linear regression
• Introduction to Multiple Linear regression
• Analysis of Variance and Linear regression

Logistic Regression Analysis

• Revisit binary outcomes: OR, RR, Risk difference
• Introduction to Logistic regression

Further topics:

• Introduction to Non-parametric tests
• Sample Size Issues
• Writing a statistical report

Assessment

Task Length % of module mark
Essay/coursework
Analysis Report
N/A 90
Essay/coursework
Online Quizzes
N/A 10

Special assessment rules

Non-compensatable

Reassessment

Task Length % of module mark
Essay/coursework
Analysis Report
N/A 90

Module feedback

Written feedback for summative assessment is provided on the standard proforma, within the timescale specified in the programme handbook.

Recommended text for students

• Altman DG. Practical statistics for medical research. London: Chapman and Hall, 1995.
• Bland M. An introduction to medical statistics; Oxford: Oxford University Press
• Cumming, Geoff . Understanding the new statistics: effect sizes, confidence intervals, and meta-analysis. New York ; London : Routledge
• Other recommended reading

• Field, A. Discovering statistics using SPSS for Windows. Sage.
• Norman, Geoffrey R. Biostatistics: the bare essentials. Shelton, Conn : People’s Medical Pub. House
• Peacock, Janet . Presenting medical statistics from proposal to publication: a step-by-step guide. Oxford : Oxford University Press

The information on this page is indicative of the module that is currently on offer. The University is constantly exploring ways to enhance and improve its degree programmes and therefore reserves the right to make variations to the content and method of delivery of modules, and to discontinue modules, if such action is reasonably considered to be necessary by the University. Where appropriate, the University will notify and consult with affected students in advance about any changes that are required in line with the University's policy on the Approval of Modifications to Existing Taught Programmes of Study.

Coronavirus (COVID-19): changes to courses

The 2020/21 academic year will start in September. We aim to deliver as much face-to-face teaching as we can, supported by high quality online alternatives where we must.

Find details of the measures we're planning to protect our community.