BE279-7-SP-SO:
Applied Statistics and Forecasting

The details
2023/24
Essex Business School
Southend Campus
Spring
Postgraduate: Level 7
Current
Monday 15 January 2024
Friday 22 March 2024
15
29 June 2023

 

Requisites for this module
(none)
(none)
(none)
(none)

 

(none)

Key module for

MSC N11112 Business Analytics,
MSC N111JS Business Analytics,
MSC N21612 International Logistics and Supply Chain Management

Module description

This module provides students with a number of key skills and techniques, which will enable them to make quicker and smarter decisions in the face of increasing uncertainty and complexity.


The module will focus on organising, visualising, computing, and analysing data to provide insights which can then act as inputs into the decision-making process. The approach will use both theoretical and practical concepts. It will concentrate on the applicability of a range of statistical and computational methods in data driven decision making.

Module aims

No information available.

Module learning outcomes

By the end of this module, students will be expected to be able to:



  1. Have obtained a critical understanding of principal-driven and data-driven approaches in statistical computing and modelling which can be used to analyse data for answering real-life questions.

  2. Have developed key analytical skills of analysing data using modern software tools and techniques from an application point of view.

  3. Have gained overall perspective on the importance of data analysis and statistics in both strategic and tactical decision making faced by decision makers in the modern business world.

  4. Critically differentiate between the questions which can be tackled using qualitative methods and those which require statistical analytical techniques.

Module information

The importance of data driven decision-making cannot be overstated in today's big data era. Decision makers including private equity investors, venture capitalists, analysts, entrepreneurs, management consultants, and business managers are increasingly facing a very complex business environment and have to make decisions which potentially could have a huge impact on not only the business unit in question, but also on employees, stakeholders and society at large.


While the problems have become more complex, decision makers have also at their fingertips, access to vast amounts of data as well as tools which can help them analyse the data. The ability to understand the data and use them to support their decisions is increasingly proving to be a necessary skill in a decision maker's portfolio.

Learning and teaching methods

The lectures will be developed around the key theoretical concepts of modern statistical computing and modelling, and how they are generally utilised in analysis and answer real business-oriented questions. The lecture material provides an overall view of how to use multiple methods in statistical computing and methods, based on the nature of the question posed as well as nature and source 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 to learn and practise the use of statistical methods taught in the lectures in a practical context. They will give the students hands on practice of the freely available statistics software SPSS, which has a whole range of functionalities from basic to advanced along with excellent graphing qualities.

Bibliography

This module does not appear to have any essential texts. To see non - essential items, please refer to the module's reading list.

Assessment items, weightings and deadlines

Coursework / exam Description Deadline Coursework weighting
Coursework   Individual Essay  03/05/2024  100% 

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.

Overall assessment

Coursework Exam
100% 0%

Reassessment

Coursework Exam
100% 0%
Module supervisor and teaching staff
Dr Sahar Validi, email: s.validi@essex.ac.uk.
Dr Sahar Validi
s.validi@essex.ac.uk

 

Availability
No
No
Yes

External examiner

Dr Ping Zheng
Canterbury Christ Church University
Prof Wantao Yu
University of Roehampton
Professor of Supply Chain Management
Resources
Available via Moodle
Of 30 hours, 22 (73.3%) hours available to students:
8 hours not recorded due to service coverage or fault;
0 hours not recorded due to opt-out by lecturer(s), module, or event type.

 

Further information
Essex Business School

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