Introduction to Quantitative Analysis
Essex Business School
Undergraduate: Level 4
Monday 13 January 2020
Friday 20 March 2020
11 November 2019
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 N833 Tourism Management (Including Year Abroad),
BSC N834 Tourism Management (Including Placement Year),
BSC N835 Tourism Management (Including Foundation Year),
BSC N835CO Tourism Management (Including Foundation Year)
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. 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. 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.
Broadly, the module aims to provide first year undergraduate students a broad understanding of what quantitative techniques can offer towards analysis of basic data sets they may come across – both as a student and as a professional. This includes
Appreciation of basic quantitative methods can help them collate and organize simple data sets
Introduction to visual and analytical methods of inspection of data which can provide insights otherwise difficult to obtain
Some 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
On successful completion of this module, the students should be able to
1. Develop critical understanding of why quantitative methods are important and where they are relevant
2. Have basic theoretical and practical knowledge of mathematical concepts required for more advanced quantitative techniques
3. Have basic theoretical and practical knowledge of statistical techniques which provide the first essential steps in analysing larger data sets
4. Judge and differentiate between different quantitative techniques, and what kind of problems are suited to which type of techniques
No additional information available.
Including number and format of contact hours, e.g. lectures, seminars, classes, practicals
Specify where students can find this information
The following learning and teaching methods will inform the pedagogic process of the course:
Lectures: 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.
Seminars: 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.
Assessment items, weightings and deadlines
|Coursework / exam
||120 minutes during Summer (Main Period) (Main)
Module supervisor and teaching staff
Dr Abijit Sengupta
Student Services Advisor email@example.com
No external examiner information available for this module.
Available via Moodle
Of 30 hours, 30 (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).
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