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STAT260 Visualisation and Modelling in R

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.

Paper title Visualisation and Modelling in R
Paper code STAT260
Subject Statistics
EFTS 0.1500
Points 18 points
Teaching period Second Semester
Domestic Tuition Fees (NZD) $886.35
International Tuition Fees (NZD) $3,766.35

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

katrina.sharples@otago.ac.nz

Teaching staff

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

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 markup tools. Many of the skills students learn are transportable to other statistics packages.

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:

  1. Use R programming syntax and control flow
  2. Use R to read in, manipulate, tidy, subset, recode, and write out data sets
  3. Create, interpret and customise common statistical plots
  4. Use R to fit and interpret some common statistical models
  5. Conduct simulation of data and execute numerically intensive operations
  6. Write dynamic documents that include executable code
Textbooks

To be confirmed

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Timetable

Second Semester

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

Computer Lab

Stream Days Times Weeks
Attend one stream from
A1 Tuesday 13:00-13:50 28-34, 36-41
A2 Tuesday 14:00-14:50 28-34, 36-41
A3 Tuesday 15:00-15:50 28-34, 36-41
AND one stream from
B1 Thursday 13:00-13:50 28-34, 36-41
B2 Thursday 14:00-14:50 28-34, 36-41
B3 Thursday 15:00-15:50 28-34, 36-41

Lecture

Stream Days Times Weeks
Attend
A1 Tuesday 10:00-10:50 28-34, 36-41
Thursday 10:00-10:50 28-34, 36-41