# 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 learning activities will provide students with ongoing learning through re-engagement with prior module learning and introductory material for subsequent weeks’ learning.

## Full module specification

Module title: Statistics for Business BEM1024 1 2022/3 Dr Steven Boyne - Convenor 15 7.5 This module is not available to Maths students. Cannot be taken with BEE1022 or BEA1012 or BEE1025 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.

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
321180

## Details of learning activities and teaching methods

CategoryHours of study timeDescription
Scheduled Learning and Teaching Activity22Lectures
Scheduled Learning and Teaching Activity10Tutorials
Guided Independent Study98Coursework preparation and exam revision
Guided Independent Study20Homework tasks

## 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
Report351,500 words 1,2,3,4,5,7,8 ELE and class-wide email
Short answer essay 305 answers, 150 words each 4,5,6,8 ELE and class-wide email
In-class online (ELE) multiple-choice question (MCQ) examination 3550 minutes1,3,4,5,6,7 Answers posted on ELE
0
0
0

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

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

## Re-assessment notes

Deferrals will take place as soon as possible within the same term; Referrals** and any further deferrals will take place in the August/September Reassessment Period

** If you pass the module overall you will not be referred in any component – even if you have not passed one or more individual components.

## 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

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.

25/11/2019

09/02/2021