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BU593B: DATA, EVIDENCE AND MANAGERIAL DECISIONS (2021-2022)

Last modified: 31 May 2022 13:05


Course Overview

This course provides an introduction to evidence-based decision making. It is designed based on the premise that executives can make better decisions when they believe in evidence and have the skill to use it. The course helps students to make better personal and professional decisions. In particular, the aim of this course is to enable students to solve real-world business problems or to discover new business opportunities using the available data and evidence.

Course Details

Study Type Postgraduate Level 5
Term Third Term Credit Points 15 credits (7.5 ECTS credits)
Campus Aberdeen Sustained Study No
Co-ordinators
  • Dr Ali Bayat

What courses & programmes must have been taken before this course?

  • Any Postgraduate Programme
  • Master Of Business Administration In Business Analytics

What other courses must be taken with this course?

None.

What courses cannot be taken with this course?

None.

Are there a limited number of places available?

No

Course Description

The course will introduce the notion of evidence-based decision making and asks how managers can use available data and evidence to make informed business decisions. The aim of this course is to help students acquire practical skills in tackling business problems using data, digital tools and evidence. Students will take an applied empirical approach to solve various business problems. In the way of addressing those business problems, the students will gain a broad understanding of the key data analysis techniques. Hence, this course is complementary to general management courses that equip students with management theories and models.

The course does not require an advanced knowledge of statistics, but it is expected that students are familiar with basic statistical methods and concepts.


Contact Teaching Time

Information on contact teaching time is available from the course guide.

Teaching Breakdown

More Information about Week Numbers


Details, including assessments, may be subject to change until 30 August 2024 for 1st term courses and 20 December 2024 for 2nd term courses.

Summative Assessments

Essay

Assessment Type Summative Weighting 70
Assessment Weeks Feedback Weeks

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Feedback

Feedback will be provided within 3 weeks of submission. 

Word Count 2500
Learning Outcomes
Knowledge LevelThinking SkillOutcome
Sorry, we don't have this information available just now. Please check the course guide on MyAberdeen or with the Course Coordinator

Oral Presentation: Group

Assessment Type Summative Weighting 30
Assessment Weeks Feedback Weeks

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Feedback

10 slides, 20 minutes presentation. Feedback will be provided as per the university guidelines.

Learning Outcomes
Knowledge LevelThinking SkillOutcome
Sorry, we don't have this information available just now. Please check the course guide on MyAberdeen or with the Course Coordinator

Formative Assessment

There are no assessments for this course.

Resit Assessments

Essay

Assessment Type Summative Weighting 100
Assessment Weeks Feedback Weeks

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Feedback

Feedback will be provided within three weeks after the submission.

Word Count 2500
Learning Outcomes
Knowledge LevelThinking SkillOutcome
Sorry, we don't have this information available just now. Please check the course guide on MyAberdeen or with the Course Coordinator

Course Learning Outcomes

Knowledge LevelThinking SkillOutcome
ConceptualUnderstandDemonstrate a conceptual understanding of abductive and inductive reasoning and explain their applications in managerial decision making.
ProceduralEvaluateBeing able to identify, evaluate and classify business problems, and propose specific solutions to the problems using available data enabled by digitalisation.
FactualApplyBe able to interpret and utilise the evidence extracted from data analysis reports and digital tools in accordance with the relevant management theories and the nature of the business problem.
ReflectionAnalyseBe able to make better decisions using data and analytics.

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