Most challenges that companies/organizations face today are too complex to rely on just intuition to resolve. The recent explosion of digital data provides increasingly more opportunities for organizations to make data-driven decisions. Business analytics is the intersection of business, statistics, and technology, offering new opportunities for a competitive advantage. It unlocks the predictive potential of data analysis to improve operational efficiency, strategic management, and financial performance. It is vital in preparing organizations to solve 21st-century business challenges, and participants of this module will have exposure to powerful and innovative concepts, methodologies, and tools that support scientific and data-driven decision making.
Specifically, this 10-week module aims to foster analytical and statistical thinking in business and management so that students are able to make informed decisions under uncertainty in real business settings. Students are trained to understand the need for data, the importance of data production, the omnipresence of variability, and the quantification and explanation of variability.
This course is intended for students with minimal quantitative preparations. It is designed mainly to be applied and practical. Hands-on experience using Excel is emphasized throughout the module.
This module uses a combination of lectures, seminars, cases, simulations, and exercises. It takes a hands-on approach with a variety of real-world examples and equips students with concepts and tools that can be used immediately on the job.
After taking this module, students will have a good understanding of the fundamental concepts in quantification and explanation of variability and be able to apply them in complex business and management problems. In particular, they will be able to construct random variables, formulate probability distributions, understand the concepts of correlation between random outcomes, and apply them to make better decisions in real business settings.
Moreover, they will obtain practical skills in data collection and analysis, and think statistically. In particular, they will understand the ideas behind sampling and confidence intervals, hypothesis testing and the meaning of statistical significance, be able to identify key drivers of business outcomes and make meaningful predictions using regression analysis in real decision-making.
The following topics are covered (subject to minor change):
- Central tendency and spread measures
- Basic probability theory, conditional probability and Bayes theorem
- Random variables and important distributions
- Normal distribution
- Sampling and confidence interval
- Hypothesis testing
80% is awarded on the basis of the result of an unseen 2-hour examination paper. 20% is awarded for coursework (comprising a variety of components, such as individual homework, quizzes, group-based case analysis, etc.)
Current students should refer to Moodle for specific details of the current year’s assessment.
Students will receive electronic lecture notes written by the course leader. There are several textbooks for this course.
Main reference books (at least one of them is required listed with a decreasing priority level):
Complete Business Statistics, 7th Edition, by Aczel and Sounderpandian (Irwin)
Business Statistics for Competitive Advantage with Excel 2010, Third Edition, by Cynthia Fraser, Springer 2013