GA42 Business Statistics

Module Name: 
Business Statistics
Module Code: 
GA42
Year: 
1
Teacher : 
Charles Lindveld, Ton Willems
Email address : 
Charles.lindveld@wittenborg.eu, ton.willems@wittenborg.eu
Prerequisite: 
Bachelor Degree or equivalent managerial working experience
Introduction: 
Recent years have seen a substantial increase in the availability of data from all walks of life alongside the ability to capture, store, analyse, interpret, and leverage it. Data-driven decision making has become quicker, easier, cheaper and more recognised. Statistics provides both computational and conceptual tools to extract information and value from data. As a result, statistics has become vital in a wide range of areas Business school graduates can expect to encounter statistics in several roles: as an essential tool in conducting business research, as a toolkit whose strengths and limitations must be understood before application, and as a set of concepts that can be used to guide the team-effort of analysts. This calls for a combination of basic hands-on skills, awareness of the types of tools that are available, and an understanding of the value of information in management and decision making. This module provides grounding in applied statistics (univariate and multivariate) and an overview of the tools used in business intelligence such as data-mining, machine-learning, forecasting. Prepares the student for a career in either in industry or in academia. In addition, the (supervised) research project introduces the students to the use of statistics in business research. Students will learn how to use to a wide range of statistical software such as SPSS, and specialist datamining tools for example. Key skills you will learn include data collection methods, application of statistical methods, analysis of statistical output and statistical research skills.
Goals: 
  • Be able to apply and use the main techniques of descriptive statistics to describe, visualize and analyse corporate and broader economic and social and environmental data
  • Apply understanding and knowledge of multivariate statistical techniques so as to be able to adequately interpret reports and journal articles in which these techniques have been used
  • Develop a critical mind as to the validity and reliability of published statistical data and interpretations
  • Acquire a basic knowledge and understanding of designing written surveys, sampling frameworks and sampling techniques
  • Are able to present descriptive statistical data (both in tables and graphs) and indicators within the context of business planning and business research
Content: 
  • General: overview of statistics: what is statistics about, areas of application, its role in research and business management
  • Overview of descriptive statistics; how to use them and present them. Data visualisation (basic charts, distribution plots, heat maps) and why visualisation is important Anscombe’s quartet
  • Review of probability theory in statistics, stochastic quantities, measurement level, discrete and continuous probability distributions
  • Practical: Installation instructions for statistical software: MS Excel and SPPS
  • Review of probability theory in statistics, stochastic quantities, probability
  • Discrete and continuous probability distributions. The binomial, hypergeomeric, poisson, uniform, and normal distributions. Measures of shape, quantile plots
  • Multiplication and addition of probabilities, independence, conditional probability
  • Sampling (why sample, how to sample, consequences of sampling, properties of samples)
  • Hypothesis testing and two-sample analysis
  • Regression analysis, linear models, nonlinear models, transformations
  • Analysis of variance
  • Dimension reduction of data
  • Nonparametric statistics (Understanding why and how to use chi-square tests in contingency tables. What to do when none of the other techniques applies?)
  • Critiquing statistics presented by others (Knowing where to look for problems when someone else is presenting statistics to you; Simpson’s paradox, causal versus statistical models)
Instruction / Study Load : 
  • 36 Lesson hours
  • 104 Hours of preparation, research, assignments, literature etc. *

Total 140 Hours
* Note: Research preparation and academic paper writing of 3000 words may take between 15 - 20
hours;

IBA Final Qualification Mapping: 
Mapped with numbers: 22, 23, 24, 25 and 26 See the EEG for further reference.
Teaching Language: 
English
Teaching Methods: 
  • Classroom lecturing
  • Case study discussions
  • Statistical simulations
  • Discussion sessions
  • Research Papers
  • Collaborative Learning
Module / Lecture and seminar status: 
Compulsory
Testing and assessment: 
Note: This is a Semester 2 Module 2 Assignments: Assignment 1 - Group Case Study Project Assignment 2 – Individual Paper See the section “Assessment” (below) for details and the EEG for further reference
European Credits: 
5
Required literature: 
  • Black, K , Applied Business Statistics: Making Better Business Decisions , John Wiley & Sons; 6th Edition ( 2011 ), ISBN-10: 0470505885, ISBN-13: 978-0470505885
  • Alvin C. Burns, Ronald F. Bush, Marketing Research, 6/E, Prentice Hall ( 2010) ISBN-10: 0136027040, ISBN-13: 9780136027041’