Analytical Thinking for Decision Making

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In this interactive, practical ‘Analytical Thinking for Decision Making” workshop participants learn how people make decisions using data, the language of data and how to apply a simple, structured process that shows you how to answer questions or make decision with data.

Participants will also learn to ask business-relevant data questions, obtain relevant data, make sense of the data, draw conclusions supported by data and present results to stakeholders in a way that promotes action.


This workshop is intended for people who want to better understand the relationship between data analysis and decision making with the aim of becoming a better data analyst.

Learning Outcomes

At the end of the course participants will be able to:

  • Identify and minimise the impact of cognitive bias in data-driven decision-making
  • Apply critical thinking to data analysis to ensure your conclusions are reliable and sound
  • Apply scientific thinking to data analysis by creating hypotheses which can be tested with data
  • Apply logical thinking to ensure that conclusions drawn from data analysis are logically sound
  • Apply ethical thinking to data analysis with the goal of minimising the chance of unintended consequences arising from data-driven decisions

Course Agenda

Module 1

  • Understanding Human Decision Making
  • A deeper dive into the brain’s thinking systems
  • Intuitive Thinking: When to rely and not rely on it
  • Logical Thinking: When to rely and not rely on it
  • Understanding and minimising cognitive bias
  • Critical Thinking in Data Analysis
  • Start with a good question
  • Identifying and avoiding reasoning errors
  • Evaluating your evidence
  • Scientific Thinking in Data Analysis
  • Understanding the scientific method
  • Forming a good hypothesis
  • Observation versus experiment

Module 2

  • Logical Thinking in Data Analysis
  • Deduction versus induction
  • The structure of a logical argument
  • Identifying and understanding logical fallacies
  • Statistical Thinking in Data Analysis
  • Description versus inference
  • Understanding variation
  • Distinguishing signals from noise
  • Ethical Thinking in Data Analysis
  • What is ethical thinking?
  • Why is ethical thinking needed in data analysis?
  • How to maximise the chance of ethical analysis
  • The data analyst’s code of ethics


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