A paper for students in health-related subjects, in particular nutrition, food science, epidemiology, exercise science, psychology, and the health sciences. Topics covered include the nature of random variation, the concepts of bias and confounding, study design, data description including risks and odds, binomial and normal distributions, estimation, hypothesis testing, regression, the control of confounders, critical appraisal, and the analysis of variance.
Biostatistics (statistics applied in the health sciences) is a vital tool in the mission to improve health and well-being for all people. STAT 115 provides an introduction to the core principles and methods of biostatistics. In this paper you will gain an understanding of how statistics is used to answer research questions: how to look for patterns in data and how to test hypotheses about disease causation and prevention and improvement in well-being. The program 'R' will be used throughout the paper for data summary and statistical analysis. The understanding and skills gained in STAT 115 can be a starting point for a career in biostatistics or can be used to assist understanding of research in other disciplines including epidemiology, physiology, anatomy, human nutrition, sports science and psychology.
|Paper title||Introduction to Biostatistics|
|Teaching period||Second Semester (On campus)|
|Domestic Tuition Fees (NZD)||$913.95|
|International Tuition Fees (NZD)||$4,073.40|
- STAT 110, (BSNS 102 or BSNS 112), QUAN 101
- Schedule C
- Arts and Music, Science
- Suitable for students of all disciplines with an interest in the quantitative analysis
of data, especially in the health sciences
There are no formal mathematical or statistical prerequisites for this paper, but students who have not done mathematics or statistics at NCEA Level 3 are encouraged to make use of the online and tutorial resources available as part of the paper.
- More information link
- View more information about STAT 115
- Teaching staff
- Paper Structure
- Main topics:
- Basic measures for describing data
- Introduction to statistical program 'R'
- Introduction to probability
- Binomial and normal distributions
- Estimation and confidence intervals
- Hypothesis testing
- Categorical data analysis
- Simple linear regression
- Regression procedures and the control of confounding
- The analysis of variation (ANOVA)
- Statistical issues in study design and critical appraisal of research
- Teaching Arrangements
Four lectures per week.
Cafeteria-style (voluntary attendance) tutorials each week for assistance with course material and exercises.
There is no set text. Copies of all lecture slides area available at the start of the course either in electronic or paper form
- Graduate Attributes Emphasised
- Interdisciplinary perspective, Lifelong learning, Scholarship, Critical thinking,
View more information about Otago's graduate attributes.
- Learning Outcomes
- Students who successfully complete the paper will demonstrate awareness of and proficiency in the basics of objective statistical data analysis.