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IB150-15 Foundations of Data Analysis for Management

Department
Warwick Business School
Level
Undergraduate Level 1
Module leader
Liza Konovalova
Credit value
15
Module duration
10 weeks
Assessment
Multiple
Study location
University of Warwick main campus, Coventry

Introductory description

The ability to use and make sense of quantitative information is an essential skill for any student taking a business or management degree. Foundation of Data Analysis for Management provides the students with the basic knowledge of statistics and probability.

After completing the module, the students will be able carry out analysis of data as well as be able to critically assess reported quantitative information. These skills are essential for
any career in business and management. The module provides a foundation for the term 2 module Business Analytics (IB122) and for both other modules offered in the second and third year that develop and expand on this disciplinary area.

Module web page

Module aims

The ability to use and make sense of quantitative information is an essential skill for any student taking a business or management degree. Foundation of Data Analysis for Management provides the students with the basic knowledge of statistics and probability.

After completing the module, the students will be able carry out analysis of data as well as be able to critically assess reported quantitative information. These skills are essential for
any career in business and management. The module provides a foundation for the term 2 module Business Analytics (IB122) and for both other modules offered in the second and third year that develop and expand on this disciplinary area.

Outline syllabus

This is an indicative module outline only to give an indication of the sort of topics that may be covered. Actual sessions held may differ.

Business Statistics:
Introduction to statistical analysis and modelling, data presentation, descriptive statistics, basic probability concepts, introduction to probability distributions, sampling methods, confidence intervals, hypothesis testing, introduction to regression.

Learning outcomes

By the end of the module, students should be able to:

  • Understand the importance of statistical methods for modern business practices, and be aware of the strengths and limitations of these methods.
  • Be familiar with basic statistical concepts and specific techniques.
  • Tackle real life quantitative problems and be able to convey results and discuss the issues involved.
  • Problem solving skills..

Indicative reading list

  • Siegel, A. (2016), "Practical business statistics", 7th edition, Academic Press. ISBN 9780128042502
  • Favero, L. P. (2019), "Data science for business and decision making", Academic Press. ISBN 9780128112175
  • Salkind, N. J. (2017), "Statistics for people who (think they) hate statistics", 6th edition, SAGE. ISBN 9781506361161
  • Spiegelhalter, D. (2019), “The Art of Statistics: Learning from Data”, Pelican. ISBN: 9780241398630
  • Levitt, S and Dubner, S (2009). “Freakonomics: A Rogue Economist Explores the Hidden Side of Everything”, Harper Perennial. ISBN: 978-0060731335

Subject specific skills

Apply basic quantitative tools, be aware of limitations.

Transferable skills

Use Excel for basic data analysis ranging from descriptive statistics to regression models.
Critical and logical thinking.

Study time

Type Required
Lectures 10 sessions of 1 hour (7%)
Seminars 9 sessions of 1 hour (6%)
Online learning (independent) 10 sessions of 1 hour (7%)
Private study 48 hours (32%)
Assessment 72 hours (48%)
Total 149 hours

Private study description

Private Study.

Costs

No further costs have been identified for this module.

You do not need to pass all assessment components to pass the module.

Assessment group A
Weighting Study time Eligible for self-certification
Project 90% 65 hours Yes (extension)
Participation 10% 7 hours No
Assessment group R2
Weighting Study time Eligible for self-certification
Project 100% Yes (extension)
Feedback on assessment

Markers comments uploaded to each student. Solutions to exam and markers comments put up on my.wbs.

Post-requisite modules

If you pass this module, you can take:

  • IB3BE-15 Business Experimentation for Data-Driven Decision-making
  • IB3M5-15 Advanced Analysis for Marketing Decisions
  • IB122-15 Business Analytics
Anti-requisite modules

If you take this module, you cannot also take:

  • IB149-15 Introduction to Statistics

Courses

This module is Core optional for:

  • Year 1 of UGEA-RN21 Undergraduate German and Business Studies