BSc Business Accounting with Industrial/Professional Experience

 This course introduces students to mathematical and statistical methods, including describing data, probability, hypothesis testing, correlation, and regression in the first semester, as well as functions, calculus, matrix algebra, optimization, decision making, the time value of money, and time series in the second semester. By applying these quantitative methods to accounting and finance data and solving practical examples, students will develop their analytical skills.

Core for BSc Accounting w/without IPE and BSc Business Accounting with IPE.

Core module for BSc Accounting and BSc Business Accounting. 

The unit aims to:

This course enables students to learn quantitative methods for mathematical and statistical modeling. Students comprehend how to apply these models and quantitative tools to accounting and financial data and critically analyze practical examples. 

On successful completion, students wishing to pursue a career in accounting and finance will be able to analyse problems using mathematical and statistical methods. By applying the tools covered throughout the course and using Excel spreadsheets, students will learn how to manage and analyse accounting and finance data. The course also prepares students for the second and final year courses, including BMAN23000 A & B (Foundations of Finance), BMAN30091 (Financial Derivatives), and BMAN30242 (Financial Engineering). 

Semester 1

Describing Data

Probability Theory and Random Variables

Conditional Probability and Tree Diagram

Probability Distributions

Sampling and Estimation

Confidence Interval

Hypothesis Testing

Testing Hypothesis for the mean of one sample  

Testing Hypothesis for comparing means of two samples

Covariance, Correlation, and Linear Regression.

Revision

 

Semester 2

Quadratic Equations, Functions and Curves

Univariate and Multivariate Functions

Calculus: Differentiation, Partial Differentiation, and Integration

Matrix Algebra

Business Modeling and Optimization

Linear programming

Decision Making

Time Value of Money and Asset Pricing

Time Series and Forecasting  

Simulation

Revision 

Lecture hours: 44

Seminar hours: 18

Total study hours: 200 hours split between lectures, classes, self-study and preparation for classes, coursework and examinations.

Gain the knowledge of diverse quantitative methods and understand how to analyse and interpret problems.

Apply quantitative methods to accounting and finance data for analysing practical examples.

Understand the limits of each of the quantitative methods. 

Improve their critical thinking for the decision making.

Exercise computational and problem-solving skills.  

 

Gain experience in data visualization and interpretation.

Develop and apply models for analysing practical examples.

 

Build capacity for independent learning and working with other members of a team.

Enhance their information technology skills, especially working with databases and Excel spreadsheets, in analysing and interpreting statistical results.

 

100% by exam: 2 exams with formula sheets: One in each exam period (January and May).

 

Feedback methods include providing advice and discussion during lectures by undertaking polls and solving questions during interactive seminar sessions. In addition, students can post their questions on the Blackboard discussion forum, where a teaching staff member will answer those questions. Students can also book an appointment for office hours. 

 

 

 

Textbook: Swift L and Piff S (2014). Quantitative Methods for Business, Management and Finance 4th Edition. Palgrave Macmillan: Basingstoke, Hampshire. Available as online e-textbook (Kortext) from BB module website.

Supplementary Text: Zhang, Z., & Shafer, D. (2016). Introductory Statistics. Available on the website https://stats.libretexts.org/Bookshelves/Introductory_Statistics/ Introductory_Statistics (Shafer and_ Zhang)

Dewhurst F (2006). Quantitative Methods for Business and Management, 2nd Edition. McGraw Hill: New York 
 

Pre-requisite course: n/a

Co-requisite course: n/a

Dependent courses: n/a

Programme restrictions: BSc Accounting and BSc Business Accounting students only

For Academic Year 2023/24

Updated: March 2023

Approved by: March UG Committee