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HASC413 Biostatistics

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 0.1250
Points 15 points
Teaching period First Semester
Domestic Tuition Fees (NZD) $1,216.88
International Tuition Fees (NZD) $4,934.75

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Limited to
MHealSc, MPharm, MSc, PGDipHealSc, PGDipMLSc, PGDipSci, PGDipPharm
Eligibility
Suitable for students from any disciplines who are interested in learning introductory level biostatistics. A basic knowledge of algebra is assumed.
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 epidemiological studies
  2. Descriptive statistics and graphical summaries
  3. Introduction to probability
  4. Probability distributions
  5. Sampling distributions
  6. Confidence intervals
  7. Hypothesis testing
  8. Power and sample size calculation
  9. Analyses for epidemiological studies
  10. Simple linear regression
Teaching Arrangements

Lectures twice a week, one 1.5 hours, one 50 minutes, plus computer laboratory work, 2 hours

Textbooks
Kirkwood, BR & Sterne, AC (2003) Essential Medical Statistics
Graduate Attributes Emphasised
Communication, Critical thinking, Research.
View more information about Otago's graduate attributes.
Learning Outcomes
  1. Perform basic statistical analyses to address simple research questions using a statistical software package (Stata)
  2. Understand the principles behind basic statistical analyses
  3. Understand how to interpret and present basic statistical analyses

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Course Coordinator

Dr Jimmy Zeng

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Overview

This paper will emphasise computer data analysis with the goal of providing students with the tools for basic analysis of their research projects, including statistical aspects of study design, data description, handling data on a computer, using a statistical software package, and carrying out and interpreting simple statistical analyses. Familiarity with basic mathematical concepts is essential.

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Objectives

Following completion of this course, you should be able to:

  • Understand important statistical concepts and terminology
  • Understand the basic statistical framework used in the design and analysis of health related studies
  • Use a computer software package for elementary data analysis
  • Complete a detailed statistical analysis of a simple study
  • Critically appraise scientific research from a statistical perspective
  • Understand the principles behind more complex statistical analyses
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Timetable

First Semester

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

Computer Lab

Stream Days Times Weeks
Attend
A1 Tuesday 11:00-12:50 12
Friday 11:00-12:50 9-15, 18-22

Lecture

Stream Days Times Weeks
Attend
A1 Monday 14:00-15:50 9-16, 18-22
Wednesday 10:00-10:50 9-16, 18-22

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 0.1250
Points 15 points
Teaching period First Semester
Domestic Tuition Fees Tuition Fees for 2020 have not yet been set
International Tuition Fees Tuition Fees for international students are elsewhere on this website.

^ Top of page

Limited to
MHealSc, MPharm, MSc, PGDipHealSc, PGDipMLSc, PGDipSci, PGDipPharm
Eligibility
Suitable for students from any disciplines who are interested in learning introductory level biostatistics. A basic knowledge of algebra is assumed.
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 epidemiological studies
  2. Descriptive statistics and graphical summaries
  3. Introduction to probability
  4. Probability distributions
  5. Sampling distributions
  6. Confidence intervals
  7. Hypothesis testing
  8. Power and sample size calculation
  9. Analyses for epidemiological studies
  10. Simple linear regression
Teaching Arrangements

Lectures twice a week, one 1.5 hours, one 50 minutes, plus computer laboratory work, 2 hours

Textbooks
Kirkwood, BR & Sterne, AC (2003) Essential Medical Statistics
Graduate Attributes Emphasised
Communication, Critical thinking, Research.
View more information about Otago's graduate attributes.
Learning Outcomes
  1. Perform basic statistical analyses to address simple research questions using a statistical software package (Stata)
  2. Understand the principles behind basic statistical analyses
  3. Understand how to interpret and present basic statistical analyses

^ Top of page

Course Coordinator

Dr Jimmy Zeng

^ Top of Page

Overview

This paper will emphasise computer data analysis with the goal of providing students with the tools for basic analysis of their research projects, including statistical aspects of study design, data description, handling data on a computer, using a statistical software package, and carrying out and interpreting simple statistical analyses. Familiarity with basic mathematical concepts is essential.

^ Top of Page

Objectives

Following completion of this course, you should be able to:

  • Understand important statistical concepts and terminology
  • Understand the basic statistical framework used in the design and analysis of health related studies
  • Use a computer software package for elementary data analysis
  • Complete a detailed statistical analysis of a simple study
  • Critically appraise scientific research from a statistical perspective
  • Understand the principles behind more complex statistical analyses
  • ^ Top of Page

^ Top of page

Timetable

First Semester

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

Computer Lab

Stream Days Times Weeks
Attend
A1 Friday 11:00-12:50 9-14, 17-22

Lecture

Stream Days Times Weeks
Attend
A1 Monday 14:00-15:50 9-15, 17, 19-22
Tuesday 15:00-15:50 9-15, 17-22