Introduction to Quantitative Analysis
Essex Business School
Undergraduate: Level 4
Thursday 05 October 2023
Friday 15 December 2023
21 June 2023
Requisites for this module
BBA N100 Business Administration,
BBA N103 Business Administration (Including Placement Year),
BBA N104 Business Administration (Including Foundation Year),
BBA N104CO Business Administration (Including Foundation Year),
BBA N110 Business Administration (Including Year Abroad),
BSC N120 International Business and Entrepreneurship,
BSC N121 International Business and Entrepreneurship (Including Year Abroad),
BSC N123 International Business and Entrepreneurship (Including Placement Year),
BSC N124 International Business and Entrepreneurship (Including Foundation Year),
BSC N124CO International Business and Entrepreneurship (Including Foundation Year),
BSC N501 Marketing,
BSC N502 Marketing (Including Year Abroad),
BSC N504 Marketing (Including Placement Year),
BSC N505 Marketing (Including Foundation Year),
BSC N505CO Marketing (Including Foundation Year),
BSC N832 Tourism Management,
BSC N834 Tourism Management (Including Placement Year),
BSC N355 International Business and Finance,
BSC N356 International Business and Finance (Including Placement Year),
BSC N357 International Business and Finance (Including Year Abroad),
BSC N358 International Business and Finance (Including Foundation Year),
BSC N358CO International Business and Finance (Including Foundation Year),
BSC N111 Business Administration and Supply Chain Management,
BSC N112 Business Administration and Supply Chain Management (Including Placement Year),
BSC N113 Business Administration and Supply Chain Management (Including Year Abroad),
BSC N114 Business Administration and Supply Chain Management (Including Foundation Year),
BSC N114CO Business Administration and Supply Chain Management (Including Foundation Year)
This module aims to provide some basic understanding to the wide variety of techniques available for analysis in business management, especially relevant in today's data driven society, where large, complex data sets are ubiquitous.
The aims of this module are:
- To provide a broad understanding of what quantitative techniques can offer towards analysis of basic data sets.
- An appreciation of basic quantitative methods can help collate and organize simple data sets.
- An introduction to visual and analytical methods of inspection of data which can provide insights otherwise difficult to obtain.
- To provide hands on exercises with basic but critical analytical tools such as MS Excel and statistical software such as R, SPSS, Stata, SAS, which can be easily used for basic data analysis.
- Basic statistical concepts such central tendency, variation, distributions, correlations.
- Basic mathematical concepts such as algebraic manipulation, solving simple equations, graphing and coordinate geometry, standard functional forms.
By the end of this module, students will be expected to be able to:
- Develop critical understanding of why quantitative methods are important and where they are relevant.
- Have basic theoretical and practical knowledge of mathematical concepts required for more advanced quantitative techniques.
- Have basic theoretical and practical knowledge of statistical techniques which provide the first essential steps in analysing larger data sets.
- Judge and differentiate between different quantitative techniques, and what kind of problems are suited to which type of techniques.
Quantitative methods are an essential feature of research and practise in all fields of social sciences, including business and management studies. However, the term encompasses a wide range of methodologies, techniques and analytical paradigms, each of which is relevant for specific problems, specific areas and disciplines.
Students will be provided an orientation on thinking and analysing quantitatively, given a basic understanding of where and how quantitative methods are relevant and what tools are available in order to carry out very basic analysis. It would also include a primer on basic mathematical and numerical concepts, which would be crucial for other modules and courses being taught in the business school.
This module will be delivered via:
- One lecture per week.
- One seminar per week.
The lectures will be developed around the key theoretical concepts of quantitative methods. It will also address the issue of multiplicity of analytical requirements when it concerns actual practical applications, and hence will provide a rounded view of how to choose between different methodologies, based on the nature of the question posed as well as nature of available data.
The seminars will focus on practical aspects of using the material taught in lectures for solving real life problems. They will use freely available datasets in addition to established software toolkits, at a very basic level, understanding the results of such analysis and evaluating them in the context of business problems.
This module does not appear to have a published bibliography for this year.
Assessment items, weightings and deadlines
|Coursework / exam
Exam format definitions
- Remote, open book: Your exam will take place remotely via an online learning platform. You may refer to any physical or electronic materials during the exam.
- In-person, open book: Your exam will take place on campus under invigilation. You may refer to any physical materials such as paper study notes or a textbook during the exam. Electronic devices may not be used in the exam.
- In-person, open book (restricted): The exam will take place on campus under invigilation. You may refer only to specific physical materials such as a named textbook during the exam. Permitted materials will be specified by your department. Electronic devices may not be used in the exam.
- In-person, closed book: The exam will take place on campus under invigilation. You may not refer to any physical materials or electronic devices during the exam. There may be times when a paper dictionary,
for example, may be permitted in an otherwise closed book exam. Any exceptions will be specified by your department.
Your department will provide further guidance before your exams.
Module supervisor and teaching staff
Dr Shabneez Bhankaraully, email: firstname.lastname@example.org.
Dr Shabneez Bhankaraully
Dr Fangming Xu
University of Bristol
Associate Professor of Finance
Available via Moodle
Of 29 hours, 29 (100%) hours available to students:
0 hours not recorded due to service coverage or fault;
0 hours not recorded due to opt-out by lecturer(s), module, or event type.
Disclaimer: The University makes every effort to ensure that this information on its Module Directory is accurate and up-to-date. Exceptionally it can
be necessary to make changes, for example to programmes, modules, facilities or fees. Examples of such reasons might include a change of law or regulatory requirements,
industrial action, lack of demand, departure of key personnel, change in government policy, or withdrawal/reduction of funding. Changes to modules may for example consist
of variations to the content and method of delivery or assessment of modules and other services, to discontinue modules and other services and to merge or combine modules.
The University will endeavour to keep such changes to a minimum, and will also keep students informed appropriately by updating our programme specifications and module directory.
The full Procedures, Rules and Regulations of the University governing how it operates are set out in the Charter, Statutes and Ordinances and in the University Regulations, Policy and Procedures.