In the terminology that we have developed, John Snow conducted an observational study, not a randomized experiment. But he called his study a “grand experiment” because, as he wrote, “No fewer than three hundred thousand people … were divided into two groups without their choice, and in most cases, without their knowledge …”

Studies such as Snow’s are sometimes called “natural experiments.” However, true randomization does not simply mean that the treatment and control groups are selected “without their choice.”

The method of randomization can be as simple as tossing a coin. It may also be quite a bit more complex. But every method of randomization consists of a sequence of carefully defined steps that allow chances to be specified mathematically. This has two important consequences.

  1. It allows us to account—mathematically—for the possibility that randomization produces treatment and control groups that are quite different from each other.

  2. It allows us to make precise mathematical statements about differences between the treatment and control groups. This in turn helps us make justifiable conclusions about whether the treatment has any effect.

In this course, you will learn how to conduct and analyze your own randomized experiments. That will involve more detail than has been presented in this chapter. For now, just focus on the main idea: to try to establish causality, run a randomized controlled experiment if possible. If you are conducting an observational study, you might be able to establish association but it will be harder to establish causation. Be extremely careful about confounding factors before making conclusions about causality based on an observational study.


  • observational study
  • treatment
  • outcome
  • association
  • causal association
  • causality
  • comparison
  • treatment group
  • control group
  • epidemiology
  • confounding
  • randomization
  • randomized controlled experiment
  • randomized controlled trial (RCT)
  • blind
  • placebo

Fun facts

  1. John Snow is sometimes called the father of epidemiology, but he was an anesthesiologist by profession. One of his patients was Queen Victoria, who was an early recipient of anesthetics during childbirth.

  2. Florence Nightingale, the originator of modern nursing practices and famous for her work in the Crimean War, was a die-hard miasmatist. She had no time for theories about contagion and germs, and was not one for mincing her words. “There is no end to the absurdities connected with this doctrine,” she said. “Suffice it to say that in the ordinary sense of the word, there is no proof such as would be admitted in any scientific enquiry that there is any such thing as contagion.”

  3. A later RCT established that the conditions on which PROGRESA insisted—children going to school, preventive health care—were not necessary to achieve increased enrollment. Just the financial boost of the welfare payments was sufficient.

Good reads

The Strange Case of the Broad Street Pump: John Snow and the Mystery of Cholera by Sandra Hempel, published by our own University of California Press, reads like a whodunit. It was one of the main sources for this section's account of John Snow and his work. A word of warning: some of the contents of the book are stomach-churning.

Poor Economics, the best seller by Abhijit Banerjee and Esther Duflo of MIT, is an accessible and lively account of ways to fight global poverty. It includes numerous examples of RCTs, including the PROGRESA example in this section.