Introduction to Statistics for Accountants

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 and non-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 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.


Full module specification

Module title:Introduction to Statistics for Accountants
Module code:BEA1012
Module level:1
Academic year:2016/7
Module lecturers:
  • Mr Ian Andrews - Convenor
Module credit:15
ECTS value:






Duration of module: Duration (weeks) - term 1:


Module aims

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.

ILO: Module-specific skills

  • 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 of non-parametric hypothesis testing
  • 6. use and critically evaluate tools such as correlation analysis, analysis of variance and regression

ILO: Discipline-specific skills

  • 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

  • 8. apply quantitative, computational and written communication skills

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 tutorial 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
Case Study251000 words1-8Written feedback to each group: gorup size 4-6 students
Examination (multiple choice and non-multiple choice questions)752 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
Case study and final examExamination (100%) 2 hour closed book exam1-8August Examination Period

Syllabus plan

  • Defining and collecting data
  • Organising and visualizing 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, uniform, exponential, and approximations to the binomial distribution
  • 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
  • Simple and multiple regression models and testing

Indicative learning resources - Basic reading

Indicative readings:

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

Barrow, M. (2013). Statistics for Economics, Accounting and Business Studies, 6th edition, Pearson, 482 pp

Levine, D. M. Stephan, D. F. and Szabat, K. A. (2014), Statistics for Managers using Microsoft Excel, 7th Edition, Harlow: Pearson Education Limited ISBN: 978-0-273-78711-2

ELE – resources on BEA1012

Module has an active ELE page?


Origin date


Last revision date