Quantitative Methods for Business Decisions

Module   Code

FINU9QA

Semester                   

Autumn

Prerequisites             

ACCU9A1 or ACCU9A2

SCQF   Level

10

Credit   value

20

Module Co-ordinator           

Miss Catherine Howie

Lecturers                   

Miss Catherine Howie

Assessment    

40% Coursework, 60% Examination

Module introduction, aims and objectives

The course is intended to give students:

  • a basis for the analysis and interpretation of quantitative information
  • an understanding of the basic ideas underlying statistical methods at an introductory level.
  • an understanding of certain mathematical tools of business decision making

The course is for students who want an introductory course in statistics / quantitative methods relating to business, or who need such a course to meet professional accounting body requirements.

Learning outcomes and skills developed

  • Calculate descriptive statistical measures and appreciate the uses and limitations of the measures.
  • Compute standard index numbers and discuss the features of different reported index numbers in the finance area.
  • Understand and apply basic concepts of probability and theoretical probability (binomial, normal but not poisson) distributions.
  • Understand basic ideas of sampling theory and test hypotheses concerning means and proportions, involving one or two samples.
  • Calculate a simple ordinary least squares regression model with one explanatory variable, apply the model, and calculate the correlation coefficient between two variables.
  • Interpret the results of multiple regression models; understand at a basic level the assumptions inherent in such models and their application in macroeconomic modelling.
  • Recognise situations in which non-parametric statistics might be more appropriate.
  • Understand the basic principles of decision theory, apply various decision criteria, and use decision trees to assist in sequential decisions.
  • Use a computer package to carry out statistical analysis on larger, more realistic, data sets.
  • Apply quantitative models (linear programming and network analysis) at an introductory level, with emphasis on relevant data and the limitations of the techniques.

Introductory Reading

The following textbook is required reading for the module:

J. Curwin, R. Slater & D Eadson Quantitative Methods for Business Decisions (7th Revised Edition) Cengage Learning

 

This module information is representative of what is included in the module in a given year. Details of actual reading, lectures and coursework may vary year to year and will be available at the beginning of the semester.

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