DATAB8003 - Quantitative Techniques

Module Details

Module Code: DATAB8003
Full Title: Quantitative Techniques
Valid From:: Semester 1 - 2016/17 ( September 2016 )
Language of Instruction:English
Duration: 1 Semester
Credits:: 10
Module Owner:: Colette Henry
Departments: Unknown
Module Description: no description provided
 
Module Learning Outcome
On successful completion of this module the learner will be able to:
# Module Learning Outcome Description
MLO1 Present and summarise statistical data using suitable graphs and measures of Central Tendency and Dispersion.
MLO2 Use statistical modelling methods (Regression, Correlation & Time Series) to identify patterns within data and project realistic business estimates.
MLO3 Use probability distributions (binomial, poisson and normal)and how they are used in Probability modelling.
MLO4 Use differential calculus to assist in solving problems relating to Demand, Revenue, Cost and Profit functions.
MLO5 Demonstrate ability to analyse financial data using discounting and compounding.
MLO6 Use Linear Programming (Graphical and Simplex algorithm) to be able to maximise/minimise Profit/Cost problems with given restrictions
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
Content
• Data formatting and illustration. • Statistical analysis of data. • Time Series analysis. • Regression & Correlation applications. • Index Numbers and the commonly used Price Indices. • Nominal and effective interest rates. Net Present value. Depreciation. Discounted cash flow. Internal rates of return. • Annuities, Mortgage payments, Investment appraisal. • Use of differential calculus to the solution of cost, revenue, profit functions and in the calculation of inventory problems. • Use of linear programming to solve constrained industrial problems.
Module Assessment
Assessment Breakdown%
Course Work40.00%
Final Examination60.00%
Module Special Regulation
 

Assessments

Full-time

Course Work
Assessment Type Class Test % of Total Mark 10
Marks Out Of 100 Pass Mark 40
Timing S1 Week 5 Learning Outcome 1,2,3
Duration in minutes 75
Assessment Description
Class test
Assessment Type Class Test % of Total Mark 10
Marks Out Of 100 Pass Mark 40
Timing S1 Week 13 Learning Outcome 4,5,6
Duration in minutes 75
Assessment Description
Class test
Project
Assessment Type Project % of Total Mark 20
Marks Out Of 100 Pass Mark 40
Timing S1 Week 14 Learning Outcome 1,2,3,4,5,6
Duration in minutes 0
Assessment Description
An individual assignment covering all topics
No Practical
Final Examination
Assessment Type Formal Exam % of Total Mark 60
Marks Out Of 0 Pass Mark 0
Timing End-of-Semester Learning Outcome 1,2,3,4,6
Duration in minutes 0
Assessment Description
End-of-Semester Final Examination
Reassessment Requirement
A repeat examination
Reassessment of this module will consist of a repeat examination. It is possible that there will also be a requirement to be reassessed in a coursework element.

DKIT reserves the right to alter the nature and timings of assessment

 

Module Workload

This module has no Full-time workload.
Workload: Part-time
Workload Type Contact Type Workload Description Frequency Average Weekly Learner Workload Hours
Lecture Contact Facilitated learning using a variety of interactive pedagogical techniques. Every Week 3.00 3
Directed Reading Non Contact Prescribed reading on the subject area as directed by the module leader. Every Week 6.00 6
Independent Study Non Contact Wider reading and reflection on the subject area using a variety of methods. Particular focus will be placed on application of learning. Every Week 6.00 6
Total Weekly Learner Workload 15.00
Total Weekly Contact Hours 3.00
 
Module Resources
Recommended Book Resources
  • Francis, Andre. (2005), Business Mathematics and Statistics, Sixth. Thomson Learning, UK.
Supplementary Book Resources
  • Louise Swift. (2001), Quantitative Methods for Business, Management & Finance, First. Palgrave, UK.
  • Lind, Marchal & Wathen. (2003), Basic Statistics for Business & Economics, Fourth. McGraw-Hill, USA.
  • Booth & Turner. (1996), Business Mathematics with Statistics, First. Pitman, UK.
This module does not have any article/paper resources
This module does not have any other resources