module specification

To be successful in business one needs to be able to deal with numbers and understand statistics, and the various ways in which they are presented. Innovation and entrepreneurship come from creativity, and from understanding trends that are visible in data available through business and industry statistics.
This module introduces data collection and presentation skills in the context of the travel and tourism industry. It provides underpinning skills required to deal with numerical information and to make effective use of mathematical and statistical methods of data analysis and interpretation relevant to the industry.  In other words, it provides students with an understanding of the fundamentals of statistical methods necessary for the travel and tourism industry.
Overall, this module provides analytical and communications skills relevant to understanding industry information with an emphasis on problem-solving techniques used in aviation and tourism industries.

Basic Mathematics and Statistics Skills

The travel and tourism industries and the need for quantitative analysis
Databases in Aviation, Travel and Tourism
Basic business mathematics and statistics in the travel and tourism industries
Expressions in mathematics using variables 

Equations and inequalities
Statistical fundamentals – with application in the travel and tourism industries
Sampling, questionnaire design and survey techniques – passengers opinion LO1
Modelling transport, airlines management and decision-making process
Use of correlation, regression and time series analysis
Linear and quadratic functions –  revenue evaluation and management 
Demand and cost – demand for air travel, cost and pricing
Forecasting through decomposition and additive/multiplicative process
Organisations that carry out statistical analyses in the travel and tourism industries LO2

The formal delivery of the teaching and learning will consist of three-hour weekly workshops involving lecture/seminar periods, and include lectures, guest speakers, case study discussions, panel discussions and debates, film and DVDs, as well as scenario-based activities and simulations.

Within the module there is significant opportunity to participate in proactive learning activities via the use of Weblearn facilities which promote inter-active discussions between both peers and lecturers and enables learners to share resources and access links to external journal articles, websites and other sources.

Discussion and debate are actively encouraged both within the classroom context and via Weblearn (VLE). Students participating in this degree come from a variety of backgrounds and often have a wealth of industry experience upon which to draw. It is useful to access this via our VLE’s proactive and inter-active classroom management. Students are responsible to prepare for forthcoming lectures to ensure that they fully understand the concepts discussed and can participate fully in debates and discussions.

Tutors will provide an indication of forthcoming lecture content at the end of each preceding lecture. The student should then research articles and appropriate readings around these themes to contribute fully to discussions and inter-active Question and Answer sessions.

Opportunities for reflective learning will be available throughout the module as students will consider their approach to tasks and discussions whilst simultaneously reflect upon informal feedback from lecturers on ideas and concepts spoken in class, and on assessments.

On successful completion of this module students will be able to:
1. Understand mathematical and statistical methods to analyse data and explore relationships between different variables using excel
2. Comprehend the means by which data can be collected, summarised and presented in reports to inform management decision making

The assessment strategy will be based on two elements including an in-class test and a piece of coursework:
• An in-class test to cover the fundamentals of statistics
• The individual piece of coursework requires the application of statistical techniques such as correlation, regression and time series analysis in the context of travel and tourism industries

Core Texts (Essential):
• Buglear, J. (2010) Stats means business: Statistics with Excel for business, hospitality and tourism, Butterworth-Heinemann.
• Oakshott, L. (2016). Essential Quantitative Methods for Business, Management and Finance, 6th ed., Palgrave Macmillan.
• Swift, L., Piff, S. (2014), Quantitative Methods for Business, Management and Finance, 4th ed., UK: Palgrave Macmillan.
Other Texts (Recommended):
• Anderson, D.R., Sweeney, D.J., Williams, T.A., Freeman, J., Shoesmith, E. (2017) Statistics for Business and Economics, 4th ed., Cengage Learning.
• Buglear, J. (2011) Quantitative Methods for Business and Management, Pearson.
• Dewhurst, F. (2006) Quantitative Methods for Business and Management, 2nd ed., McGraw Hill.
• Rowntree, D. (2004) Statistics without Tears: An introduction for non-mathematicians, Penguin.
• Taylor, S. (2007) Business Statistics for non-mathematicians, 2nd ed., Palgrave Macmillan.
• Waters, D. (2011) Quantitative Methods for Business, 5th ed., Financial Times: Prentice Hall.
Electronic Databases and Websites:
• Bank of England database; www.bankofengland.co.uk
• EU database Eurostat; http://ec.europa.eu/eurostat, especially Tourism statistics; http://ec.europa.eu/eurostat/statistics-explained/index.php/Tourism and Air transport statistics; http://ec.europa.eu/eurostat/statistics-explained/index.php/Air_transport_statistics
• Office for National Statistics; https://www.ons.gov.uk
• Statista; https://www.statista.com/topics/3670/airline-industry-uk/
• Yahoo finance; http://uk.finance.yahoo.com