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Essential analytical methods necessary for health-related research: data description, basic probability, confidence intervals, hypothesis testing, sample size calculation, epidemiological measures of association, and simple linear regression. A knowledge of basic algebra is recommended.

This paper provides an introduction to the use of statistical methods to answer specific research questions in health-related areas.

Paper title Biostatistics
Paper code HASC413
Subject Health Sciences
EFTS 0.125
Points 15 points
Teaching period Semester 1 (On campus)
Domestic Tuition Fees (NZD) $1,311.38
International Tuition Fees Tuition Fees for international students are elsewhere on this website.

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Limited to
MHealSc, MPharm, MSc, PGDipHealSc, PGDipMLSc, PGDipSci, PGDipPharm, BMLSc(Hons)
Eligibility

Suitable for students who are interested in upgrading their statistical skills for carrying out health-related quantitative research.

Contact
jimmy.zeng@otago.ac.nz
Teaching staff
Convenor and Lecturer: Jiaxu Zeng
Paper Structure

This paper covers the following main topics:

  1. Introduction to biostatistics
  2. Descriptive analysis
  3. Introduction to diagnostic testing
  4. Probability distributions
  5. Sampling distributions
  6. Confidence intervals
  7. Hypothesis testing
  8. Power and sample size calculation
  9. Introduction to epidemiological studies
  10. Critical appraisal of health research
Textbooks

Altman, Douglas G (1990) Practical Statistics for Medical Research

Graduate Attributes Emphasised
Communication, Critical thinking, Research.
View more information about Otago's graduate attributes.
Learning Outcomes

Students who successfully complete this paper will:

  • Perform basic statistical analyses to address simple research questions using a statistical software package (Stata)
  • Understand the principles behind basic statistical analyses
  • Understand how to interpret and present basic statistical analyses

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Timetable

Semester 1

Location
Dunedin
Teaching method
This paper is taught On Campus
Learning management system
Moodle

Computer Lab

Stream Days Times Weeks
Attend
A1 Friday 10:00-11:50 9-13, 16-22

Lecture

Stream Days Times Weeks
Attend
A1 Monday 14:00-15:50 9-14, 16-22