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Unit information: Advanced Quantitative Analysis in Management in 2021/22

Please note: you are viewing unit and programme information for a past academic year. Please see the current academic year for up to date information.

Unit name Advanced Quantitative Analysis in Management
Unit code EFIM20039
Credit points 20
Level of study I/5
Teaching block(s) Teaching Block 1 (weeks 1 - 12)
Unit director Dr. Mansi
Open unit status Not open
Pre-requisites

60% in EFIM10014 Quantitative Analysis in Management

Co-requisites

None

School/department School of Management - Business School
Faculty Faculty of Social Sciences and Law

Description including Unit Aims

The aim of this unit is to build on students’ introductory understanding of statistical analysis from EFIM10014 Quantitative Analysis in Management. The intention is to equip students with the ability to conduct dissertation-level research in branches of management requiring significant quantitative analysis. The module focuses on how to specialist software (SPSS and Stata) to perform statistical analysis and how to interpret the resulting analyses; how to model and analyse the relationships within business data, particularly multivariate relationships; and how to make correct inferences from the data (and recognise incorrect analysis). The unit utilises advanced computer modelling tools beyond Microsoft Excel to analyse and present quantitative data. It therefore develops practical skills in statistical and mathematical techniques that support specialist management analysis and decision making. It draws on advanced quantitative analysis and business statistics theories with contemporary computational skills to critically evaluate complex business problems and to cross-examine them through computer technologies. The unit will also prepare students for the reading, comprehension and interpretation of original business and management research articles that are based on quantitative data and statistical analysis.
Indicative course content:


SPSS and Stata functions for statistical analysis

Multiple Linear and non-Linear regression analysis

ANOVA and other hypothesis testing.

Factor Analysis

Cluster Analysis

Intended Learning Outcomes

Students should be able to:

1. Appraise the capabilities and differences between statistical software.

2. Evaluate the scope and nature of different advanced statistical techniques

3. Analyse Statistical models for both univariate and multivariate data.

Having successfully completed the unit, students will be able to:

4. Apply statistical techniques to business and management problems

5. Use SPSS and Stata to perform statistical analysis.

6. Evaluate and Communicate quantitative ideas effectively both in oral and written form

Teaching Information

Teaching will be delivered through a combination of synchronous and asynchronous sessions including lectures, tutorials, drop-in sessions, discussion boards and other online learning opportunities.

Assessment Information

Coursework: portfolio of three activities (100%). This assesses all of the learning outcomes.

The whole portfolio should not exceed 30 pages (this is an indicative guide, as the portfolio will consist of graphs, figures, tables, equations and commentary on these).

Resources

If this unit has a Resource List, you will normally find a link to it in the Blackboard area for the unit. Sometimes there will be a separate link for each weekly topic.

If you are unable to access a list through Blackboard, you can also find it via the Resource Lists homepage. Search for the list by the unit name or code (e.g. EFIM20039).

How much time the unit requires
Each credit equates to 10 hours of total student input. For example a 20 credit unit will take you 200 hours of study to complete. Your total learning time is made up of contact time, directed learning tasks, independent learning and assessment activity.

See the Faculty workload statement relating to this unit for more information.

Assessment
The Board of Examiners will consider all cases where students have failed or not completed the assessments required for credit. The Board considers each student's outcomes across all the units which contribute to each year's programme of study. If you have self-certificated your absence from an assessment, you will normally be required to complete it the next time it runs (this is usually in the next assessment period).
The Board of Examiners will take into account any extenuating circumstances and operates within the Regulations and Code of Practice for Taught Programmes.

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