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    Overview

    Introduction to the use of statistical methods in health sciences research. Descriptive and simple inferential statistics for discrete, continuous and right-censored data. Introduction to linear regression.

    This distance-taught paper will introduce students to the use of statistical methods in health sciences research and is highly recommended for all students that want and/or need to analyse quantitative data. Students will learn the theory needed to perform basic descriptive analysis and to begin to understand appropriate statistical methods to quantitative questions. The paper has a strong applied component, and students will learn how the foundations of biostatistics apply to public health. Topics covered include: descriptive statistics, hypothesis testing and analysis for epidemiological studies. Students will learn to use Stata, a leading statistical software package in health sciences research. For this paper, students must have a computer with an Internet connection and be computer literate.

    About this paper

    Paper title Applied Biostatistics 1 - Fundamentals
    Subject Public Health
    EFTS 0.125
    Points 15 points
    Teaching period 1st Non standard period (29 April 2024 - 28 June 2024) (Distance learning)
    Domestic Tuition Fees ( NZD ) $1,551.63
    International Tuition Fees Tuition Fees for international students are elsewhere on this website.
    Restriction
    HASC 413
    Limited to
    MA, MAppSc, MClinPharm, MHealSc, MMLSc, MPH, MPharm, MPHC, MSc, DPH, PGDipAppSc, PGDipArts, PGDipHealSc, PGDipMLSc, PGDipPharm, PGDipSci, PGCertPH, BMLSc(Hons)
    Eligibility

    Students who have completed an undergraduate degree in any discipline or recognised equivalent.

    Contact

    Department of Preventive and Social Medicine, Dunedin campus: publichealth.dunedin@otago.ac.nz

    Teaching staff

    Paper Convenor: To be confirmed.

    Paper Structure

    Topics:

    1. Introduction to Biostatistics
    2. Descriptive Statistics and Graphical Summaries
    3. Sampling Distributions
    4. Confidence Intervals
    5. Hypothesis Testing and Sample Size
    6. Analysis for epidemiological studies

    Assessment Structure:

    1. Participation and contribution: 10% of the marks for this paper will derive from your contribution to Zoom sessions and discussion forums. The marks will not be awarded for the correctness of your contributions, but for making an effort to engage with the question at hand and to use the reading and other learning that you have done to progress the discussion.
    2. Assignment 1: This assignment, worth 40% of the mark for the paper, assesses your ability to perform descriptive statistics and to report summaries on high-quality tables and plots. It will cover material up until the end of week 3.
    3. Assignment 2: This assignment, worth 50% of the mark for the paper, will assess your learning on material covered in the course, with an emphasis on materials covered from week 4.
    Teaching Arrangements

    This Distance Learning paper is taught remotely.

    1. Compulsory webinar sessions: Tuesday afternoons, 4pm-6pm.
    2. Block Week (zoom webinars): Monday 29th April, Tuesday 30th April, Wednesday 1st May, 4pm-6pm.
    Textbooks

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

    Graduate Attributes Emphasised
    Interdisciplinary perspective, Lifelong learning, Scholarship, Critical thinking, Information literacy, Research, Self-motivation.
    View more information about Otago's graduate attributes.
    Learning Outcomes

    Students who successfully complete the paper will be able to:

    • Demonstrate an understanding of types of data and appropriate descriptive statistics and graphical summaries.
    • Apply skills in simple data analysis methods and measures of precision and interpreting the results.
    • Demonstrate and apply understanding of the statistical issues in research design and data analysis.

    Timetable

    1st Non standard period (29 April 2024 - 28 June 2024)

    Location
    Dunedin
    Teaching method
    This paper is taught through Distance Learning
    Learning management system
    Moodle
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