STAT40830 Adv Data Prog with R (online)

Academic Year 2021/2022

In this module we cover advanced use of R and Rstudio, following on from the Data Programming with R module. Topics are subject to change each year as the software progresses but are likely to include:
- Professional graphics through ggplot2
- Use and configuration of R
- Advanced function behaviour
- Different ways to access R and Rstudio
- Advanced data processing with R through dplyr
- Creating interactive documents and presentations with Rstudio, markdown and knitr

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Curricular information is subject to change

Learning Outcomes:

By the end of the module students should be have attained considerable mastery in R. They should be able to produce professional quality data analytics and documents via Rstudio which are suitable for use in a business environment.

Student Effort Hours: 
Student Effort Type Hours
Specified Learning Activities

24
Autonomous Student Learning

72
Online Learning

24
Total

120
Approaches to Teaching and Learning:
Weekly video lectures, weekly computer labs, homework assignments. 
Requirements, Exclusions and Recommendations
Learning Requirements:

Students must have completed one of the modules Data Programming or Data Programming with R


Module Requisites and Incompatibles
Not applicable to this module.
 
Assessment Strategy  
Description Timing Open Book Exam Component Scale Must Pass Component % of Final Grade
Project: Final project. Varies over the Trimester n/a Other No

70
Continuous Assessment: Homework assignments and small projects. Varies over the Trimester n/a Other No

30

Carry forward of passed components
No
 
Resit In Terminal Exam
Autumn No
Please see Student Jargon Buster for more information about remediation types and timing. 
Feedback Strategy/Strategies

• Group/class feedback, post-assessment

How will my Feedback be Delivered?

Not yet recorded.

Name Role
Dr Emma Howard Lecturer / Co-Lecturer
John O'Sullivan Lecturer / Co-Lecturer