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Introduction to Health Statistics - HEA00091M

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  • Department: Health Sciences
  • Module co-ordinator: Prof. Catherine Hewitt
  • Credit value: 10 credits
  • Credit level: M
  • Academic year of delivery: 2021-22
    • See module specification for other years: 2022-23

Related modules

Pre-requisite modules

  • None

Co-requisite modules

  • None

Prohibited combinations


Module will run

Occurrence Teaching period
A Autumn Term 2021-22

Module aims

To provide students with basic skills to carry out their own research projects including designing a questionnaire, collecting data, processing and undertaking basic statistical analysis in SPSS. The students will also gain the ability to read health research papers and will be introduced to the basic ideas of statistical analysis and presentation.

Module learning outcomes

Upon completion of the module, students should know, understand or be able to do the following:

  1. Be able to critically appraise the design of a questionnaire.
  2. Demonstrate understanding of basic statistical analysis.
  3. Be able to select and conduct the appropriate statistical analysis for a research question.
  4. Know which output from basic summaries and statistical analysis should be presented and the appropriate format to use.
  5. Be able to appraise the appropriateness and interpretation of basic statistical analysis in health research papers.

Module content

Sessions will include:

Questionnaire design: Importance of clarity and fairness, types of question, scales, validity, coding, sensitive questions. Design of a health questionnaire. Sample size determination.

Summary statistics, normal distribution and introduction to SPSS: Simple data summaries in SPSS. The normal distribution, standard errors, quantiles and variance.  Distribution of questionnaires and discussion of formative assessment.

Comparing means: Independent t tests. Confidence intervals and p-values.

Comparing means: One sample t test and paired t tests. Forest plots as used in trial reports. 

Correlation: Scatter diagrams and correlation coefficients.

Chi-squared and Fisher’s exact tests: Chi-squared and Fisher’s exact tests, including SPSS crosstabs.

Statistics in practice: Critical appraisal of statistical methods covered in this module in published research. 

Assessment

Task Length % of module mark
Online Exam - 24 hrs (Centrally scheduled)
Introduction to Health Statistics		 N/A 100

Special assessment rules

None

Reassessment

Task Length % of module mark
Online Exam - 24 hrs (Centrally scheduled)
Introduction to Health Statistics		 N/A 100

Module feedback

Students are provided with collective exam feedback relating to their cohort, within the timescale specified in the programme handbook.

Indicative reading

  • Altman, D.G. (1991). Practical statistics for medical research. London: Chapman and Hall.
  • Bland, M. (2000). An introduction to medical statistics. 3rd edn. Oxford: Oxford University Press. (new edition due in 2015).
  • Field, A. (2013). Discovering Statistics Using IBM SPSS Statistics. SAGE.
  • Pallant, J. (2013). SPSS survival manual: a step by step guide to data analysis using IBM SPSS. 5th edn. Open University Press.
  • Peacock, J. and Peacock, P. (2010). Oxford handbook of medical statistics. Oxford: Oxford University Press.
  • Peacock, J. and Kerry S. (2007). 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.