Statistics for Business
This module will familiarise students with the principles and practice of performing statistical analyses within a range of management, marketing and business analytics settings. The module introduces students to the ways in which statistical analyses and hypothesis testing can contribute to business knowledge. Discipline-relevant examples from the research literature will be used to illustrate practical applications of statistics and students will gain practical experience in how to perform statistical analyses through software-based tutorial sessions using IBM SPSS (Statistical Package for the Social Sciences). Weekly structured homework tasks will provide students with ongoing learning through re-engagement with prior module learning and introductory material for subsequent weeks’ learning.
Please note that this module cannot be taken with Introduction to Statistics (BEE1022).
Full module specification
|Module title:||Statistics for Business|
This module is not available to Maths students.
Cannot be taken with BEE1022 or BEA1012
|Duration of module:||
Duration (weeks) - term 2: |
The module aims to provide: a strong foundational knowledge regarding the importance of statistical analyses; how to apply statistical analyses within management, marketing and business analytics settings; and how statistics are used in decision-making processes.
The module focuses on the practical application of statistics for improving our understanding of a range of management, marketing and business analytics issues. A strong emphasis is placed on the correct selection of statistical tests, how tests are conducted, and the subsequent interpretation of estimates (outputs). Through an introduction to research philosophy, students will learn how statistical analysis contributes to management and marketing research, analytics and knowledge.
The module draws upon a series of core textbooks (available from the library in electronic format) and a range of research articles drawn from management and organisational studies and from marketing research sources.
The module content draws upon the module convenor’s analytical experience from academic work in marketing-related social science research and organisational studies.
The content of this module is globally applicable with examples drawn from studies set in locations around the world.
Knowledge of statistics is essential for any management, marketing or business analytics student. Accordingly, this module provides students with a valuable theoretical and practical understanding of the subject, as well as weekly tasks that provide a structured framework for students to engage with the learning materials and also to expand their knowledge beyond the module readings.
All lecture notes and tutorial materials are available on the ELE (Exeter Learning Environment).
ILO: Module-specific skills
- 1. correctly select, perform and critically appraise a range of parametric and non-parametric statistical tests;
- 2. perform database management and generate descriptive statistics to characterise and summarise a data set;
- 3. apply and critically evaluate a range of statistical analyses to management, marketing and business analytics issues using the IBM SPSS software package;
- 4. understand and apply the principles of hypothesis testing and survey design.
ILO: Discipline-specific skills
- 5. explain the role of numerical evidence in the business and management environment;
- 6. discuss the paradigmatic (ontological, epistemological and methodological) positioning of quantitative and hypothesis-testing analytics in organisational, management and marketing studies.
ILO: Personal and key skills
- 7. implement a range of quantitative, computational and computer literacy skills;
- 8. demonstrate 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 Activity||22||Lectures|
|Scheduled Learning and Teaching Activity||10||Tutorials|
|Guided Independent Study||98||Coursework preparation and exam revision|
|Guided Independent Study||20||Homework tasks|
|Form of assessment||Size of the assessment (eg length / duration)||ILOs assessed||Feedback method|
|Mid-term online (ELE) multiple-choice question (MCQ) quiz||50 minutes||1,3,4,5,6,7||ELE and in-class|
|Homework tasks and online fora/learning journals||120 minutes per week||1,2,3,4,5,7,8||ELE and in-class|
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|
|Report||35||1,500 words||1,2,3,4,5,7,8||ELE and class-wide email|
|Short answer essay||30||5 answers, 150 words each||4,5,6,8||ELE and class-wide email|
|In-class online (ELE) multiple-choice question (MCQ) examination||35||50 minutes||1,3,4,5,6,7||Answers posted 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|
|Report||Report (1,500 words; 35%)||1,2,3,4,5,7,8||August/September Reassessment Period|
|Short answer essay||Short answer essay (5 answers, 150 words each; 30%)||4,5,6,8||August/September Reassessment Period|
|In-class online (ELE) multiple-choice question (MCQ) examination||In-class online (ELE) multiple-choice question (MCQ) examination (50 minutes; 35%)||1,3,4,5,6,7||August/September Reassessment Period|
- Statistics and the philosophy of research
- The nature of data and principles of hypothesis testing
- Database and data management with SPSS
- Descriptive statistics for business and management
- Parametric statistical tests 1: t-test, ANOVA and Pearson’s correlations
- Parametric statistical tests 2: regression analysis and an introduction to multivariate statistics (exploratory and confirmatory factor analysis and structural equation modelling)
- Non-parametric statistical tests: Mann-Whitney, Kruskal-Wallis and Kendall’s tau
- Survey design for statistical analysis
- Statistical analysis in marketing research
- Introduction to statistics for Business Analytics
- Reporting statistical findings
Indicative learning resources - Basic reading
Basic reading. The main texts that the module will draw upon are:
Ho, R. (2017). Understanding statistics for the social sciences with IBM SPSS: Boca Raton: CRC Press.
Kraska-Miller, M. (2014). Nonparametric statistics for social and behavioral sciences: Boca Raton: CRC Press.
Sarstedt, M., & Mooi, E. (2019). A Concise Guide to Market Research: The Process, Data, and Methods Using IBM SPSS Statistics. Berlin: Springer. http://encore.exeter.ac.uk/iii/encore/record/C__Rb4015242
Module has an active ELE page?
Indicative learning resources - Web based and electronic resources
The module will also draw upon a range of web-based and electronic resources
Indicative learning resources - Other resources
The module will also draw upon a range of research articles from the organisational, management and marketing studies literature.
Last revision date