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University of Exeter Business School

Introduction to Statistics for Accountants

Module titleIntroduction to Statistics for Accountants
Module codeBEA1012
Academic year2023/4
Module staff

Mr Ian Andrews (Convenor)

Duration: Term123
Duration: Weeks


Number students taking module (anticipated)


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.


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.


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.


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 ActivitiesGuided independent studyPlacement / study abroad

Details of learning activities and teaching methods

CategoryHours of study timeDescription
Scheduled Learning and Teaching20Lectures
Scheduled Learning and Teaching10Tutorials
Scheduled Learning and Teaching1Revision
Guided Independent Study119Reading, question practice and assessment preparation

Formative assessment

Form of assessmentSize of the assessment (eg length / duration)ILOs assessedFeedback method
Short form questions 1 hour1-8In class and correct answers on ELE

Summative assessment (% of credit)

CourseworkWritten examsPractical exams

Details of summative assessment

Form of assessment% of creditSize of the assessment (eg length / duration)ILOs assessedFeedback method
In-class assessment 201 hour1-8Mark awarded and suggested solutions
Written examination802 hours1-8Correct answers on ELE

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

Original form of assessmentForm of re-assessmentILOs re-assessedTimescale for re-assessment
In-class assessment In-class assessment (20%)1-8July/August Reassessment Period
Examination (multiple choice and non-multiple choice questions)Examination (80%)1-8August 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 (2nd ed.). Andover: Cengage.

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

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

ELE – resources on BEA1012

Key words search

Statistics, Accounting, Business, Finance

Credit value15
Module ECTS


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)


Available as distance learning?


Origin date


Last revision date