STAT40780 Data Prog with C (online)

Academic Year 2023/2024

The module covers the essence of programming with data using the languages C and C++, with a particular focus on incorporating such code into the R statistical environment. Students will learn the structure of both languages and how commands can be called from R via the Rcpp and inline packages. This enables a very large speed gain over traditional R commands, and is especially useful for large data sets.

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Curricular information is subject to change

Learning Outcomes:

By the end of the module students should be able to:
- Write code in both C and C++ and call such code into R
- Use the Rcpp and inline packages to export variables from C into R and vice-versa
- Use advanced features of the packages to work with large data objects and perform complex data manipulations

Student Effort Hours: 
Student Effort Type Hours
Lectures

24
Computer Aided Lab

12
Autonomous Student Learning

80
Total

116
Approaches to Teaching and Learning:
Lectures, enquiry, problem-based learning. 
Requirements, Exclusions and Recommendations
Learning Requirements:

Students should have completed a previous R programming module


Module Requisites and Incompatibles
Not applicable to this module.
 
Assessment Strategy  
Description Timing Open Book Exam Component Scale Must Pass Component % of Final Grade
Multiple Choice Questionnaire: 5 short MCQs Varies over the Trimester n/a Standard conversion grade scale 40% No

10
Practical Examination: 2 hour end of semester computer lab exam Unspecified n/a Standard conversion grade scale 40% No

60
Continuous Assessment: Computer lab exercises Throughout the Trimester n/a Standard conversion grade scale 40% No

30

Carry forward of passed components
No
 
Resit In Terminal Exam
Autumn Yes - 2 Hour
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 Marie Galligan Lecturer / Co-Lecturer
Dr James Herterich Lecturer / Co-Lecturer
Dr Emma Howard Lecturer / Co-Lecturer
Mr Brian Buckley Tutor
Timetabling information is displayed only for guidance purposes, relates to the current Academic Year only and is subject to change.
 

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