Module Details

Module Code: STAT6015
Title: Analytics for Tourism
Long Title: Analytics for Tourism
NFQ Level: Fundamental
Valid From: Semester 1 - 2024/25 ( September 2024 )
Duration: 1 Semester
Credits: 5
Field of Study: 4620 - Statistics
Module Delivered in: no programmes
Module Description: This module will provide learners with insights into the use of statistics and analytics in the context of Tourism and Hospitality. Students will receive a foundation in statistics and the role that data can play in business decisions.
 
Learning Outcomes
On successful completion of this module the learner will be able to:
# Learning Outcome Description
LO1 Apply the methods of descriptive statistics to organise, summarise, present and analyse data.
LO2 Calculate and interpret summary statistics.
LO3 Collect, manage, manipulate and present data.
LO4 Use software to sort, filter, analyse and visualise real world data.
Dependencies
Module Recommendations

This is prior learning (or a practical skill) that is strongly recommended before enrolment in this module. You may enrol in this module if you have not acquired the recommended learning but you will have considerable difficulty in passing (i.e. achieving the learning outcomes of) the module. While the prior learning is expressed as named MTU module(s) it also allows for learning (in another module or modules) which is equivalent to the learning specified in the named module(s).
Incompatible Modules
These are modules which have learning outcomes that are too similar to the learning outcomes of this module. You may not earn additional credit for the same learning and therefore you may not enrol in this module if you have successfully completed any modules in the incompatible list.
No incompatible modules listed
Co-requisite Modules
No Co-requisite modules listed
Requirements

This is prior learning (or a practical skill) that is mandatory before enrolment in this module is allowed. You may not enrol on this module if you have not acquired the learning specified in this section.
No requirements listed
 
Indicative Content
Types of Data
Introduction to Qualitative and Quantitative data - overview of nominal, ordinal, discrete, and continuous data types. Differences between structured and unstructured data in the context of real world data.
Descriptive Statistics
Data collection methods. Measures of central tendency and other measures of location, advantages and disadvantages. Measures of dispersion, range, and standard deviation.
Exploratory Data Analysis Tools
Presentation of data in the form of charts and graphs, including scatter plots, histograms, ogives, bar charts, pictograms, linear fits.
Laboratory programme
Calculations applied to a business/tourism setting. Exploration of data using pivot tables - creating data tables, sorting and filtering data, slicers, pivot charts and dashboard creation.
Statistical Anlaysis
Analysis of data using statistical tools.
Module Content & Assessment
Assessment Breakdown%
Coursework100.00%

Assessments

Coursework
Assessment Type Practical/Skills Evaluation % of Total Mark 20
Timing Week 4 Learning Outcomes 1,2
Assessment Description
Excel assessment on descriptive statistics
Assessment Type Practical/Skills Evaluation % of Total Mark 20
Timing Week 8 Learning Outcomes 3
Assessment Description
Excel assessment on data presentation
Assessment Type Project % of Total Mark 40
Timing Week 12 Learning Outcomes 1,2,3,4
Assessment Description
Analyse a real world dataset, create an interactive dashboard and report on the results.
Assessment Type Presentation % of Total Mark 20
Timing Week 12 Learning Outcomes 1,2,3,4
Assessment Description
Presentation of results from dataset analysed as part of the project.
No End of Module Formal Examination
Reassessment Requirement
Coursework Only
This module is reassessed solely on the basis of re-submitted coursework. There is no repeat written examination.

The University reserves the right to alter the nature and timings of assessment

 

Module Workload

Workload: Full Time
Workload Type Contact Type Workload Description Frequency Average Weekly Learner Workload Hours
Lecture Contact Delivery of content and material underpinning learning outcomes Every Week 2.00 2
Lab Contact Practical skills development Every Week 2.00 2
Independent & Directed Learning (Non-contact) Non Contact Review of course material Every Week 3.00 3
Total Hours 7.00
Total Weekly Learner Workload 7.00
Total Weekly Contact Hours 4.00
Workload: Part Time
Workload Type Contact Type Workload Description Frequency Average Weekly Learner Workload Hours
Lecture Contact Delivery of content and material underpinning learning outcomes Every Week 1.50 1.5
Lab Contact Practical skills development Every Week 1.50 1.5
Independent & Directed Learning (Non-contact) Non Contact Review of course material Every Week 4.00 4
Total Hours 7.00
Total Weekly Learner Workload 7.00
Total Weekly Contact Hours 3.00
 
Module Resources
Recommended Book Resources
  • Andre Francis,Ben Mousley. (2014), Business Mathematics and Statistics, Cengage Learning EMEA, [ISBN: 1408083159].
  • Mark L. Berenson,David M. Levine,Kathryn A. Szabat,David F. Stephan. (2019), Basic Business Statistics, Global Edition, 14th. Pearson, [ISBN: 1292265035].
Supplementary Book Resources
  • David R. Anderson,Dennis J. Sweeney,Thomas A. Williams,James J. Cochran,Jeffrey D. Camm. (2020), Essentials of Modern Business Statistics with Microsoft Office Excel, 8th. South-Western College Publishing, [ISBN: 0357131622].
This module does not have any article/paper resources
Other Resources