Statistics for Business II

Course Description & Learning Outcomes

Over the course of three days, you will explore multiple statistical concepts and learn how to apply them to business use cases. You will work on cleaning and preparing the data for analysis and generating insights. You will experience the use of data visualisation to find answers to business questions. You will learn how to discover correlations in data and to build simple linear regression models. Finally, you will learn about supervised and unsupervised machine learning techniques. Here you will practice building classification trees to predict customer behavior or condition; and using cluster analysis methods to create customer groupings that would lead to more effective customer management and engagement. All the topics taught will be delivered through a problem-based approach and active discussions that are driven by use of numerous business scenarios. Emphasis is placed on critical thinking, practice skills and practical knowledge with the use of software and tools only as delivery mechanisms. This course is part of the Data Science Series and Graduate Certificate in Analytics Project Management offered by NUS-ISS. At the end of the course, participants will learn: - How statistics is being applied to solve a variety of business problems - How to compute and interpret data summaries- numerically as well as visually - How visual data exploration is used to find answers to business problems - How to present data visually for better understanding of relationships between variables - How to statistically analyze whether there is a relationship between two variables and determine the size of the relationship - How to predict one variable in terms of another to make improvement in business performance - How to perform classification and prediction using decision tree modeling approach - How to cluster data into homogenous subsets to enable focused group-based customer management