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MM1F13 - Business Statistics

MM1F13-Business Statistics

Module Provider: International Business and Strategy
Number of credits: 20 [10 ECTS credits]
Level:4
Terms in which taught: Autumn / Spring term module
Pre-requisites:
Non-modular pre-requisites:
Co-requisites:
Modules excluded:
Current from: 2020/1

Module Convenor: Dr Karina Pavlisa

Email: k.pavlisa@henley.ac.uk

Type of module:

Summary module description:

Business Statistics forms a 20 credit module of Part 1 of various degree programmes within the Henley Business School. It aims to provide students with a solid knowledge of business statistics and the ability to apply these skills to real problems. The module will raise awareness of how statistics can be applied to business and behavioural issues. In the first part of the module students learn basic statistical techniques. In the second part of the module students undertake a group research project which requires them to seek out and critically evaluate published literature on a particular topic, develop a methodology and analyse data. The module enables students to practise report-writing skills, manage research activities and critically assess the outcomes from the project.? 



 



This module is delivered at University of Reading and University of Reading Malaysia.


Aims:


  • Provide solid knowledge of business statistics and the ability to apply these skills to real life problems. 

  • Raise awareness of how statistics can be applied to Business and Behavioural Issues

  • Enable students to conduct research and apply the knowledge into practice through a group research  project. 



 


Assessable learning outcomes:

On completion of this module, the student should be able to:




  • Analyse, interpret and extrapolate numeric data

  • Apply this understanding to the process of recording, analysing, summarising and presenting statistical data

  • Design and execute small scale research projects in the field of business

  • Identify, formulate and solve business decision making and management problems using appropriate statistical models.

  • Develop an understanding of the research topic subject matter 

  • Develop and acquire new skills in conducting research? 

  • Plan and manage a systematic approach to a research project? 

  • Carry out a critical review of literature 

  • Critically approach a research problem? 

  • Manage research activities  

  • Evaluate the findings of the project and provide their critical ap praisal 


Additional outcomes:
Workshops and assignments are designed to encourage the development of oral communication, written presentation skills, and student effectiveness in group situations. Structured activities are designed to develop independent learning skills. IT skills are developed by the use of the Blackboard course management system.

Outline content:
Data collection, data sampling, data sources, presenting numerical information, summarising data, measures of central tendency, measures of dispersion, distributions, probability, regression analysis, time series analysis and forecasting, correlation, probability, probability distributions, estimation, and hypothesis testing.

Brief description of teaching and learning methods:

Contact hours:
  Autumn Spring Summer
Lectures 10 5
Tutorials 4 6
Guided independent study:      
    Wider reading (independent) 18
    Wider reading (directed) 20
    Advance preparation for classes 8 12
    Preparation for tutorials 20
    Revision and preparation 25
    Essay preparation 72
       
Total hours by term 0
       
Total hours for module 200

Summative Assessment Methods:
Method Percentage
Written assignment including essay 50
Class test administered by School 50

Summative assessment- Examinations:

Summative assessment- Coursework and in-class tests:

Class Test - To be held during week 11 of Autumn Term



Written assignment includes the two parts – the Research Proposal (10% of the module mark, to be submitted  by week 5 of Spring Term) and the Final Report (40% of the module mark), to be submitted by week 11 of Spring Term


Formative assessment methods:
Students will be assessed on the basis of their project; testing their ability to formulate, plan and evaluate business research topics, and to perform basic numeric operations, and consequently analyse and interpret data in quantitative models of business and management situations.

Penalties for late submission:

The Module Convenor will apply the following penalties for work submitted late:

  • where the piece of work is submitted after the original deadline (or any formally agreed extension to the deadline): 10% of the total marks available for that piece of work will be deducted from the mark for each working day[1] (or part thereof) following the deadline up to a total of five working days;
  • where the piece of work is submitted more than five working days after the original deadline (or any formally agreed extension to the deadline): a mark of zero will be recorded.
The University policy statement on penalties for late submission can be found at: http://www.reading.ac.uk/web/FILES/qualitysupport/penaltiesforlatesubmission.pdf
You are strongly advised to ensure that coursework is submitted by the relevant deadline. You should note that it is advisable to submit work in an unfinished state rather than to fail to submit any work.

Assessment requirements for a pass:
A minimum mark of 40%

Reassessment arrangements:

By component failed. Re-assessment for Part 1 modules takes place in August of the same year.


Additional Costs (specified where applicable):

Calculator : £15 (Casio FX-83GTPLUS, Casio FX-85GTPLUS, Casio Fx-83GTx or Casio Fx-85GTx)



Core textbook: £33.99.  Dawn Willougby (2015) An Essential Guide to Business Statistics (paperback) (some copies are available in the UoR library).


Last updated: 14 July 2020

THE INFORMATION CONTAINED IN THIS MODULE DESCRIPTION DOES NOT FORM ANY PART OF A STUDENT'S CONTRACT.

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