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Curricular information is subject to change
By the end of the course you should have enough grasp of R to complete a simple statistical project: tidying your data, graphing it and analysing it econometrically.Indicative Module Content:
1. Tidying data.
2. Graphing data.
3. Ordinary least squares.
4. Time series.
5. Other regression techniques.
6. Basic machine learning.
|Student Effort Type||Hours|
|Autonomous Student Learning||
Not applicable to this module.
|Description||Timing||Component Scale||% of Final Grade|
|Project: The student will be required to submit a short project based on the material covered in the course.||Coursework (End of Trimester)||n/a||Graded||Yes||
|Resit In||Terminal Exam|
• Feedback individually to students, post-assessment
Not yet recorded.