Introduction to Statistics for Accountants
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.
Full module specification
|Module title:||Introduction to Statistics for Accountants|
This module is for Accounting students only
Non-requisites: Cannot be taken with BEE1022, BEE1025 or BEM1024.
|Duration of module:||
Duration (weeks) - term 1: |
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 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 Activities||Guided independent study||Placement / study abroad|
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|
|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|
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|
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|
If you pass the module overall you will not be referred in either component – even if you have not passed one of the components.
- 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
Indicative learning resources - Basic reading
Illowsky, B. and Dean, S. (2018). Introductory Statistics. Houston: Rice University
Lowry, R. (2020). Concepts and Applications of Inferential Statistics
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
Module has an active ELE page?
Last revision date