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    Overview

    An introduction to computer skills needed for the statistical sciences, using the software R. Covers reproducible research, data wrangling, visualisation, exploratory data analysis, resampling and simulation.

    Fundamental to modern statistical practice is proficiency in the use of specialised software packages. This paper introduces students to the world of statistical computing, which encompasses fundamental programming skills motivated by handling and manipulating data, and how this relates to exploratory data analysis, visualisation, model fitting, and numerical simulation. Focus is on implementation in the R language and associated mark-up tools. Many of the skills students learn are transportable to other statistics packages.

    About this paper

    Paper title Visualisation and Modelling in R
    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.
    Prerequisite
    (BSNS 102 or BSNS 112 or STAT 110 or STAT 115) and 54 additional points
    Restriction
    STAT 380
    Schedule C
    Arts and Music, Science
    Contact

    xun.xiao@otago.ac.nz

    Teaching staff

    Dr Tilman Davies

    Professor Matthew Schofield

    Textbooks

    To be confirmed

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

    Upon successful completion of the paper, the student will possess a range of skills used in and motivated by modern data analysis. They will be able to:

    • Use R programming syntax and control flow
    • Use R to read, manipulate, tidy, subset, recode, and write out data sets
    • Create, interpret and customise common statistical plots
    • Use R to fit and interpret some common statistical models
    • Conduct simulation of data and execute numerically intensive operations
    • Write dynamic documents that include executable code
    Assessment details

    The course has three components: exam (E), assignments (A) and mid-term test (T). The exam is worth 50% of your final grade, the assignments are worth 35% and the mid-term test is worth 15%. You must achieve a minimum score of 40% on the exam in order to pass the paper. Put another way, the final mark (F) is
    F = (50E + 35A + 15T)/100 if E ≥ 40% and
    F = Failed Compulsory if E < 40%

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