Faculty of Medical and Health Sciences


POPLHLTH 706 - Statistics in Health Science

15 Points

Semester 1

Tāmaki

Description


Provides an overview of statistics and statistical methods for health scientists. Covers basic methods and tests, including regression.

Programme and course advice


Mathematics is kept to a minimum and there is no difficult mathematics but students should have achieved NCEA level 2 or higher in mathematics or statistics. Additional basic tutorials will be offered if necessary.

This course is:

  • One of the required research methods courses for Postgradaute Diploma and Masters of Public Health
  • A useful course for students whose thesis required quantitative data analysis (including PhD students)
  • Optional research course for public health and health sciences diplomas
  • Optional course for Postgraduate Certificate in Public Health in Effective Practice specialisation

Course aims


Content outline

The course has eight 3 hour sessions.

Session 1 Introduction to Statistics. Scope, samples, variability. Data. Variables, observations, data types in health applications

Session 2 Stata software. Descriptive health statistics. Summarising and presenting data. Graphics.

Session 3 Notions of probability and independence. Relevance to diagnostic tests, disease-exposure association

Probability distributions. Discrete, continuous. Normal model and tables.

Session 4 Independence in two-way tables. Chi-square measure of non-independence. Meaning of p-value for chi-square and in general.

Session 5 Estimation Sample v population quantities. Sampling variability. Standard errors. Estimation of prevalence and means. Standard error of mean. Confidence intervals and interpretation.

Session 6 Simple Linear Regression. Straight line model through a scatter plot. Correlation. Fitting straight lines. Multiple regression extension. Confounding

Session 7 Logistic regression. When outcome is binary. Estimation of odds ratios. Other Regression issues. Regression analysis and model building

Session 8 Review of course. Examination preparation

 

Goals of the course

The course addresses practical and theoretical aspects of statistics in health sciences. Students will learn how to interpret medical and epidemiological data and understand the statistical ideas that are commonly reported in medical research reports. Practical skills in the use of a statistical analysis package (Stata) will be developed.

 

Learning outcomes 

  • To understand the rationale of and requirement for statistical methods in health analysis
  • Appreciate the importance of statistics in the analysis of clinical, epidemiological and public health data
  • Be able to choose an appropriate statistical method to analyse health data
  • Be able to use a computer program (Stata) to display, analyse data and to explore relationships between variables

Learning and teaching


This course is delivered in eight teaching sessions in a computer laboratory on Tāmaki Campus. The lecture dates are:

  • Wednesday 9:30am to 12:30pm February 28, March 14, 21, April 18, May 2, 9, 16, 23
  • Tutorials: Wednesday 2.30pm to 3.30pm February 28, March 14, 21, April 18, May 2, 9, 16, 23 

Please see your timetable on SSO or Building 730 Reception noticeboard on the day for the room details.

Learning resources

Statistics for Health Sciences Lecture Notes, by Roger Marshall, is the essential text.

e-Copies of this text and all PowerPoint slides used in the lectures will be provided via Canvas, as well as supplementary notes and other learning material. These, with Statistics for Health Sciences Lecture Notes, will be sufficient for the course. However, students may find benefit in other sources.

Good books are:

  • Medical Statistics: A Common-sense Approach. Michael Campbell and David Machin. Wiley and Sons.
  • An Introduction to Medical Statistics Martin Bland. Oxford Medical Press.
  • Practical Statistics for Medical Research. Douglas Altman, Chapman-Hall, 1991
  • Interpretation and uses of Medical Statistics. LE Daly and GJ Bourke, Blackwell Science

Stata statistical software will be used. It is available on Tāmaki computers but students may wish to purchase their own license, cost is a special price of about $200.

Assessment 

Coursework (50%) and a 2 hour examination (50%). Students will be expected to complete and hand in four equal valued assignments for the coursework component.

The semester 1 examination period is 15 June – 3 July. Note that the examination timetables are not finalised and available to students until 6-8 weeks into the semester.

Course Coordinator


Course Administrator


Email: pgpophealth@auckland.ac.nz

Phone: +64 (0) 9 9232760