Table of Contents:
  • List of figures
  • List of tables
  • Acknowledgements
  • Introduction
  • Getting things in proportion: categorical data and percentages
  • Summarizing and communicating numbers. Lots of numbers
  • Why are we looking at data anyway? Populations and measurements
  • What causes what?
  • Modelling relationships using regression
  • Algorithims, analytics and prediction
  • How sure can we be about what is going on? Estimates and intervals
  • Probability the language of uncertainty and variability
  • Putting probability and statistics together
  • Answering questions and claiming discoveries
  • Learning from experience the Bayesian Way
  • How things go wrong
  • How we can do statistics better
  • In conclusion
  • Glossary
  • Notes
  • Index.