Statistics for Business

Module description

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
Module code:BEM1024
Module level:1
Academic year:2020/1
Module lecturers:
  • Dr Steven Boyne - Convenor
Module credit:15
ECTS value:

7.5

Pre-requisites:

This module is not available to Maths students.

Co-requisites:

Cannot be taken with BEE1022,BEE1025 or BEA1012

Duration of module: Duration (weeks) - term 2:

11

Module aims

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.

 

Additional Information:

Research-enriched learning

The module content draws upon the module convenor’s analytical experience from academic work in marketing-related social science research and organisational studies.

Internationalisation

The content of this module is globally applicable with examples drawn from studies set in locations around the world.

Employability

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.

Sustainability

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 ActivitiesGuided independent studyPlacement / study abroad
301200

Details of learning activities and teaching methods

CategoryHours of study timeDescription
Scheduled Learning and Teaching Activity16Lectures
Scheduled Learning and Teaching Activity5Tutorials
Scheduled Learning and Teaching Activity9Digital learning
Guided Independent Study100Coursework preparation and exam revision
Guided Independent Study20Homework and online fora/learning journals

Formative assessment

Form of assessmentSize of the assessment (eg length / duration)ILOs assessedFeedback method
Mid-term online (ELE) multiple-choice question (MCQ) quiz50 minutes1,3,4,5,6,7ELE and in-class
Homework tasks and online fora/learning journals120 minutes per week1,2,3,4,5,7,8ELE and in-class

Summative assessment (% of credit)

CourseworkWritten examsPractical exams
65350

Details of summative assessment

Form of assessment% of creditSize of the assessment (eg length / duration)ILOs assessedFeedback method
Short answer tasks305 answers, 150 words each4,5,6,8ELE and class-wide email
In-class online (ELE) multiple-choice question (MCQ) examination 3550 minutes1,3,4,5,6,7Answers posted on ELE
Report351,500 words1,2,3,4,5,7,8ELE and class-wide email

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

Original form of assessmentForm of re-assessmentILOs re-assessedTimescale for re-assessment
Short answer tasksShort answer tasks (5 answers, 150 words each; 30%)4,5,6,8August/September Reassessment Period
In-class online (ELE) multiple-choice question (MCQ) examination In-class online (ELE) multiple-choice question (MCQ) examination (50 minutes; 35%)1,3,4,5,6,7August/September Reassessment Period
ReportReport (1,500 words; 35%)1,2,3,4,5,7,8August/September Reassessment Period

Syllabus plan

  • 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.

http://encore.exeter.ac.uk/iii/encore/record/C__Rb3949482

 

Kraska-Miller, M. (2014). Nonparametric statistics for social and behavioral sciences: Boca Raton: CRC Press.

http://encore.exeter.ac.uk/iii/encore/record/C__Rb3918127

 

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?

Yes

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.

Origin date

25/11/2019

Last revision date

03/03/2020