Biomaterials|Health Sciences|Medicine|Nutrition|Public Health|Sport and Exercise Science|Subjects Allied to Medicine

This module offers a practical insight into exercise prescription in clinical contexts. Students learn to promote evidence-based physical activity...

This module offers a practical insight into exercise prescription in clinical contexts. Students learn to promote evidence-based physical activity interventions in patients to prevent and treat chronic diseases, and thereby help tackle the public health and economic burden of common non-communicable diseases.

 

Aims - This module aims to provide an introduction to the basic mathematical aspects of sample survey design and statistical analysis, to the practical aspects...

Aims - This module aims to provide an introduction to the basic mathematical aspects of sample survey design and statistical analysis, to the practical aspects involved in carrying out a survey and to some key concepts in measurement theory. It is primarily intended for second and third year students registered on the undergraduate degree programmes offered by the Department of Statistical Science, or jointly with other departments. It also serves as an optional module for students taking the mathematics and statistics stream of the Natural Sciences degree (with prerequisite: STAT0005).

Objectives - On successful completion of the module, a student should have an understanding of the basic principles and methods underlying sample surveys, be able to assess the appropriateness of various sampling schemes and to calculate precisions and sample sizes required to achieve specific precisions or costs, to have a basic understanding of the ideas underlying the scale type classification and the concepts of validity and reliability, to construct and evaluate a Likert scale and to have a general knowledge of practical survey methods and statistics in society.

Applications - Areas of application of the methods taught in this module include governmental statistics, public health research, opinion polls, market research, and customer relationship management. Sampling techniques are also used, for example, in industrial quality control.

Content - Introduction to sampling, simple random sampling. Sources of error, practical survey methods. Planning a survey, questionnaire construction (with some philosophical background) and data collection techniques. Scale types, Likert scales, validity and reliability. Basic ideas of stratified, cluster and systematic sampling. Analysis of Social Statistics.

Key texts - Available from ReadingLists@UCL.