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Overview

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 wellbeing. 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.

About this paper

Paper title Introduction to Biostatistics
Subject Statistics
EFTS 0.15
Points 18 points
Teaching period Semester 2 (On campus)
Domestic Tuition Fees ( NZD ) $1,103.10
International Tuition Fees Tuition Fees for international students are elsewhere on this website.
Restriction
STAT 110, (BSNS 102 or BSNS 112), QUAN 101
Schedule C
Arts and Music, Science
Eligibility

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.

Contact

stat115@otago.ac.nz

Teaching staff

Associate Professor Peter Dillingham

Dr Conor Kresin

Professor Phillip Wilcox

Professor Ting Wang

Professor Matthew Schofield

Jessica Allen

Paper Structure

This paper covers:

  • Data and data summaries in biostatistics
  • Probability
  • Models for normal data
  • Confidence intervals and estimation
  • Hypothesis testing and power
  • Linear regression
  • ANOVA
  • Models for binomial and non-normal data
  • Codesigned informed by tikanga Māori
  • Sampling and study design
Teaching Arrangements

Three 1-hour lectures per week, and a 1-hour tutorial

Textbooks

There is no set text. Copies of all lecture slides are available at the start of the course either in electronic or paper form.

Graduate Attributes Emphasised
Interdisciplinary perspective, Lifelong learning, Scholarship, Critical thinking, Information literacy.
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.

Overview

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, prevention and improvement in wellbeing. 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.

About this paper

Paper title Introduction to Biostatistics
Subject Statistics
EFTS 0.1500
Points 18 points
Teaching period Semester 2 (On campus)
Domestic Tuition Fees Tuition Fees for 2027 have not yet been set
International Tuition Fees Tuition Fees for international students are elsewhere on this website.
Restriction
STAT 110, (BSNS 102 or BSNS 112), QUAN 101
Schedule C
Arts and Music, Science
Eligibility

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.

Contact

stat115@otago.ac.nz

Teaching staff

Associate Professor Peter Dillingham

Dr Conor Kresin

Professor Phillip Wilcox

Professor Ting Wang

Professor Matthew Schofield

Jessica Allen

Paper Structure

This paper covers:

  • Data and data summaries in biostatistics
  • Probability
  • Models for normal data
  • Confidence intervals and estimation
  • Hypothesis testing and power
  • Linear regression
  • ANOVA
  • Models for binomial and non-normal data
  • Codesign informed by tikanga Māori
  • Sampling and study design
Teaching Arrangements

Three 1-hour lectures per week, and a 1-hour tutorial.

Textbooks

There is no set text. Copies of all lecture slides are available at the start of the course, either in electronic or paper form.

Graduate Attributes Emphasised
Interdisciplinary perspective, Lifelong learning, Scholarship, Critical thinking, Information literacy.
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.
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