Module Details

Module Code: MATH B7009
Full Title: Business Mathematics
Valid From:: Semester 1 - 2019/20 ( June 2019 )
Language of Instruction:English
Duration: 1 Semester
Credits:: 5
Module Owner:: Brian Woods
Departments: Unknown
Module Description: The course aims to provide the student with an understanding of the basic numerical concepts and techniques relevant to the analysis of data in a business environment.
 
Module Learning Outcome
On successful completion of this module the learner will be able to:
# Module Learning Outcome Description
MLO1 Collect, collate, analyse and interpret Statistical data
MLO2 Explore bivariate relationships and generate Regression models to assist in forecasting the progression of a business.
MLO3 Investigate Business data over a time period, identify patterns and generate future projections.
MLO4 Calculate the various types of Price and Quantity Indices and interpret the effects of inflation on data over time.
Pre-requisite learning
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 DkIT module(s) it also allows for learning (in another module or modules) which is equivalent to the learning specified in the named module(s).
No recommendations listed
 
Module Indicative Content
Statistics
Generating tables,constructing graphs. Calculating and interpreting measures of Central Tendency (Mean, Mode, Median) and Dispersion (Standard Deviation and Inter-Quartile Range)
Regression & Correlation
Generating Linear Regression models graphically and algebraically and using them to obtain realistic business estimates. Using Correlation to decide on the strength of a connection between two sets of statistical data.
Time Series Modelling
Identifying patterns in time related data. Finding Trends and Seasonal Variations within the data and using them to generate suitable prediction models. Using the models to project future business figures.
Index Numbers
Understanding how to calculate and interpret simple index relatives. How to generate both fixed base and chain base index numbers over a period of time. Being able to rebase a fixed base index. Understand how to deflate business figures. Being able to generate weighted and aggregate indices.
Module Assessment
Assessment Breakdown%
Course Work100.00%
Module Special Regulation
 

Assessments

Full-time

Course Work
Assessment Type Class Test % of Total Mark 25
Marks Out Of 100 Pass Mark 40
Timing S1 Week 4 Learning Outcome 1
Duration in minutes 60
Assessment Description
1 hour written class examination
Assessment Type Class Test % of Total Mark 25
Marks Out Of 100 Pass Mark 40
Timing S1 Week 7 Learning Outcome 2
Duration in minutes 60
Assessment Description
1 hour written class examination
Assessment Type Class Test % of Total Mark 25
Marks Out Of 100 Pass Mark 40
Timing S1 Week 10 Learning Outcome 3
Duration in minutes 60
Assessment Description
1 hour written class examination
Assessment Type Class Test % of Total Mark 25
Marks Out Of 100 Pass Mark 40
Timing S1 Week 14 Learning Outcome 4
Duration in minutes 60
Assessment Description
1 hour class examination
No Project
No Practical
No Final Examination
Reassessment Requirement
No repeat examination
Reassessment of this module will be offered solely on the basis of coursework and a repeat examination will not be offered.

DKIT 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 No Description Every Week 3.00 3
Directed Reading Non Contact No Description Every Week 3.00 3
Independent Study Non Contact No Description Every Week 3.00 3
Total Weekly Learner Workload 9.00
Total Weekly Contact Hours 3.00
Workload: Part-time
Workload Type Contact Type Workload Description Frequency Average Weekly Learner Workload Hours
Lecture Contact No Description Every Week 2.00 2
Directed Reading Non Contact No Description Every Week 4.00 4
Independent Study Non Contact No Description Every Week 3.00 3
Lecture Contact Class contact hours Every Week 2.00 2
Directed Reading Non Contact Assigned worksheets Every Week 3.00 3
Independent Study Non Contact External reading material Every Week 4.00 4
Total Weekly Learner Workload 18.00
Total Weekly Contact Hours 4.00
 
Module Resources
Recommended Book Resources
  • Andre Francis & Ben Mousley. (2014), Business Mathematics and Statistics, 7th. Cengage Learning, UK, [ISBN: 9781408083154].
Supplementary Book Resources
  • Cheryl Cleaves, Margie Hobbs, Jeffrey Noble. (2013), Business Math, 10th. Prentice Hall, [ISBN: 9780135108178].
  • Paolo Brandimarte. (2011), Quantitative Methods: An Introduction for Business Management, Wiley & Sons, [ISBN: 9780470496343].
  • John Buglear. (2011), Quantitative Methods for Business and Management, Pearson, [ISBN: 9780273736288].
  • Les Oakshott. (2014), Quantitative Methods, Palgrave MacMillan, [ISBN: 9781137340856].
This module does not have any article/paper resources
This module does not have any other resources