STAT399 Special Topic: Statistical Computing

The software R is used to introduce computer skills needed for the statistical sciences. Reproducible research, visualisation, exploratory data analysis, optimisation, resampling, simulation and R programming.

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Prerequisite

(STAT 241 or STAT 210 or FINC 203 or ECON 210) and 18 additional STAT points at 200-level or above

Restriction

STAT 260, STAT 380

Schedule C

Arts and Music, Science

Contact

katrina.sharples@otago.ac.nz

Teaching staff

To be advised

Graduate Attributes Emphasised

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

Textbooks

To be advised

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. Use R to implement user-specified functions and algorithms.

4. Create, interpret and customise common statistical plots.

5. Use R to fit and interpret a range of statistical models.

6. Conduct simulation of data and execute numerically intensive operations.

7. Write dynamic documents that include executable code in LaTeX and markdown.

8. Use R to optimise functions with statistical applications.

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