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Curricular information is subject to change
On completion of this module, students should be able to understand a range of quantitative business problems and identify suitable analytics models for addressing them; and be able to explain, carry out in practice, and interpret the results of models including regression, time series forecasting, correlation, linear programming, classification, and clustering.
Student Effort Type | Hours |
---|---|
Lectures | 24 |
Small Group | 12 |
Specified Learning Activities | 36 |
Autonomous Student Learning | 40 |
Total | 112 |
Introduction to Business Analytics (1st-year module from the BSc in Quantitative Business)
Learning Recommendations:This module requires that students already have knowledge equivalent to UCD MIS10090, Data Analysis for Decision Makers -- probability and statistics, and basic Excel. The level of required mathematics is about Ordinary Level Leaving Certificate, occasionally a bit higher.
Description | Timing | Component Scale | % of Final Grade | ||
---|---|---|---|---|---|
Group Project: Large group project | Week 10 | n/a | Graded | No | 50 |
Examination: End-of-trimester online exam | 2 hour End of Trimester Exam | Yes | Graded | No | 50 |
Resit In | Terminal Exam |
---|---|
Autumn | Yes - 2 Hour |
• Feedback individually to students, post-assessment
• Group/class feedback, post-assessment
• Online automated feedback
• Self-assessment activities
Not yet recorded.
Name | Role |
---|---|
Dr Mel Devine | Lecturer / Co-Lecturer |
Ms Bing CHEN | Tutor |