Introduction to Statistics for Accountants

Module title	Introduction to Statistics for Accountants
Module code	BEA1012
Academic year	2023/4
Credits	15
Module staff	Mr Ian Andrews (Convenor)

Duration: Term	1	2	3
Duration: Weeks	11

Number students taking module (anticipated)	150

Module description

This module is an introduction to statistics and its applications to business and accounting. After initially considering descriptive statistics, we move sequentially on to probability and sampling distributions, inferential statistics (using parametric approaches) and regression. There will be a focus on understanding these concepts and methodologies intuitively with applications to management accounting, auditing and business decisions.

Internationalisation:

Statistical tools are generally applicable; scenarios for collecting and analysing data will have a mixture of UK, EU and non-EU flavours so that they are more relevant to an international student body. Collaborative work on the case study aims to bring students together from different cultural backgrounds.

Sustainability:

Availability of study materials (lecture notes, tutorial questions, readings) on ELE rather than by hard copy. Some tutorial question scenarios will reflect sustainability issues such as sourcing of materials, resource consumption and alternative energy sources.

Employability:

Student competence gained in using Microsoft Office in the completion of the case study will be useful in internships, work placements and on graduation.

Ethics and corporate responsibility:

Statistics and its use in fraud detection will be discussed in the module.

Module aims - intentions of the module

The module aims to provide students with an understanding of the role of statistical methodologies in accounting and finance through both theory and practice. Students are given the opportunity of analysing data using Excel spreadsheet software with a variety of data types and statistical models.

Intended Learning Outcomes (ILOs)

ILO: Module-specific skills

On successfully completing the module you will be able to...

1. discuss, calculate and interpret descriptive statistics
2. use probability theory and tools in business decisions
3. construct and interpret point estimates and confidence intervals
4. perform hypothesis tests and interpret test results
5. use and critically evaluate tools such as correlation analysis, analysis of variance and regression

ILO: Discipline-specific skills

On successfully completing the module you will be able to...

6. evaluate the role of numerical evidence in the accounting and business environment
7. analyse quantitative problems in business and accounting

ILO: Personal and key skills

On successfully completing the module you will be able to...

8. apply quantitative, computational and written communication skills

Syllabus plan

Defining data and related vocabulary

Organising and visualising data using tables and charts

Describing data using numerical summaries

Basic probability: simple, joint and marginal probabilities; conditional probability

Discrete probability distributions: binomial and Poisson

Continuous probability distributions: normal and uniform, and approximations to the binomial and Poisson distributions

Sampling and sampling distributions

Point and interval estimation of single population means and proportions using the normal and t-distributions; estimating sample size
One-sample hypothesis testing: single mean and proportion

Two-sample hypothesis testing: difference between two means and proportions

Chi-square and nonparametric tests

Linear regression

Learning activities and teaching methods (given in hours of study time)

Scheduled Learning and Teaching Activities	Guided independent study	Placement / study abroad
31	119	0

Details of learning activities and teaching methods

Category	Hours of study time	Description
Scheduled Learning and Teaching	20	Lectures
Scheduled Learning and Teaching	10	Tutorials
Scheduled Learning and Teaching	1	Revision
Guided Independent Study	119	Reading, question practice and assessment preparation

Formative assessment

Form of assessment	Size of the assessment (eg length / duration)	ILOs assessed	Feedback method
Short form questions	1 hour	1-8	In class and correct answers on ELE

Summative assessment (% of credit)

Coursework	Written exams	Practical exams
0	100	0

Details of summative assessment

Form of assessment	% of credit	Size of the assessment (eg length / duration)	ILOs assessed	Feedback method
In-class assessment	20	1 hour	1-8	Mark awarded and suggested solutions
Written examination	80	2 hours	1-8	Correct answers on ELE
	0
	0
	0
	0

Details of re-assessment (where required by referral or deferral)

Original form of assessment	Form of re-assessment	ILOs re-assessed	Timescale for re-assessment
In-class assessment	In-class assessment (20%)	1-8	July/August Reassessment Period
Examination (multiple choice and non-multiple choice questions)	Examination (80%)	1-8	August examination period

Re-assessment notes

If you pass the module overall you will not be referred in either component – even if you have not passed one of the components.

Indicative learning resources - Basic reading

Core texts:

Illowsky, B. and Dean, S. (2018). Introductory Statistics. Houston: Rice University

Lowry, R. (2020). Concepts and Applications of Inferential Statistics

Indicative readings:

Anderson, D.R., Sweeney, D.J., Williams, T.A., Freeman, J. and Shoesmith, E. (2010) Statistics for Business and Economics (2^nd ed.). Andover: Cengage.

Barrow, M. (2013). Statistics for Economics, Accounting and Business Studies (6^th ed.). London: Pearson.

Levine, D. M. Stephan, D. F. and Szabat, K. A. (2014), Statistics for Managers using Microsoft Excel (7^th ed.). Harlow: Pearson Education Limited

ELE – resources on BEA1012

Key words search

Statistics, Accounting, Business, Finance

Credit value	15
Module ECTS	7.5
Module pre-requisites	This module is for Accounting students only
Module co-requisites	Non-requisites: Cannot be taken with BEE1022, BEE1025 or BEM1024.
NQF level (module)	4
Available as distance learning?	No
Origin date	28/07/2015
Last revision date	20/01/2022