In this age of Big Data, how do we make sense of the abundance of readily accessible but often overwhelming quantitative information encountered at work? How do we go about systematically extracting insights from data? What does it mean to reason with data? Quantitative data reasoning can be thought of as applying a certain set of logic that allows us to work with data. In applying this logic, we make use of statistical methods and other forms of numerical analysis to answer questions that we are invested in, support or invalidate preconceived hypotheses and provide evidence to advance our arguments. The course's primary objective, therefore, is to develop the relevant skills that will allow us to apply this logic, so that we may effectively utilize data as a valuable resource to help inform and guide decision-making.
The course aims to impart quantitative data reasoning skills. These broadly encompass the ability to ask good questions; curate and organize datasets; visualize data; perform mathematical processing; carry out an analysis (eg. using models) with clear assumptions; and to communicate the results effectively.
At the end of the course, participants will be able to:
- Understand and articulate the logic that undergirds quantitative analyses.
- Demonstrate how this logic can be applicable to questions in their own professions.
- Become critical consumers of quantitative knowledge.
- Actively use data in a thoughtful, critical and reflective manner.
- The logic of reasoning quantitatively with data
- Hypothesis formulation, operationalising constructs
- Data collection and cleaning
- Use of descriptive statistics and data visualisation methods; when to use what in which situations
- The role of probability in reasoning with data
- Statistical inference – drawing conclusions from our data
- Using models – how to mathematically represent relationships in our data
- How to effectively communicate our results
Anyone who is interested in using data more effectively in their work processes
Who Should Attend
Managers, Executives, Engineers
Mode of Training
On-campus or Online (Live)