Friday, August 31, 2018
Lies, Damned Lies, and Science: How to Sort Through the Noise Around Global Warming, the Latest Health Claims, and Other Scientific Controversies (FT Press Science) 1st Edition by Sherry Seethaler (FT Press)
This is an excellent book that provides the qualitative critical thinking necessary for making better rational decisions regarding purchases, health care, and lifestyle. Many books impart the statistics to differentiate what is truly different from what is not. But, few books focus on framing the question correctly, understanding the biases of the stakeholders, and how to evaluate the findings. Ultimately, the qualitative thinking the author imparts is as important as the quantitative knowledge imparted by math books.
The author does an excellent job explaining how science works. It is a constant feedback loop of battling hypothesis and rebuttals that confuse the public. But, if you make an effort to understand the issue, you will grasp the evolving nuances of the arguments. Through this process our knowledge invariably advances.
Some highlights of the book include the matrix of stakeholders issues on page 34 regarding Global Warming, Drug approval, Genetically engineered food, and Mad cow disease. This matrix succinctly fleshes out all stakeholders positions on those four complex issues. The table of evidence being studied to understand climate change on page 83 is really thorough. Also, the concept of "pseudosymmetry of scientific authority" as explained on page 16 is interesting. It means the Media sometimes allocates as much print to both sides of an issue when the vast majority of the scientific community is on one side (that's why it is called pseudosymmetry). The entire chapter 5 on differentiating between cause and coincidence is excellent. Chapter 7 on interpreting statistics is also very good including its specific section on elucidating hidden confounding factors. Within this chapter, she also states the most important phrase in statistics: "results can be statistically significant without being statistically meaningful." Or given a large enough sample size, stat tests invariably uncover at least small differences which may be trivial. Chapter 9 is an interesting overview of widespread thinking flaws including anchoring, confirmation bias, confusing randomness for a trend, overgeneralization, and mistaking cause and effect. Those themes are now often covered in the trendy topic of behavioral economics. Chapter 10 discloses many websites that are helpful in investigating various claims.
On the other hand, I also found an error and a debatable position. On page 78, the diagram mapping out a clinical study should have Group 1 getting a placebo and Group 2 getting the drug. The diagram instead shows Group 1 receiving nothing and Group 2 receiving both the placebo and the drug. I bet this has confused many readers. Additionally, the mentioned concept of pseudosymmetry is very interesting. But, one should not immediately derive that science is a popularity contest and accept that when many more scientists are on one side of the issue they are right. This is not necessarily so. Thomas S. Kuhn, in his classic "The Structure of Scientific Revolutions," has exposed that correct new scientific ideas often come up against massive resistance from the scientific establishment hoisting the status quo. This suggests that sometimes pseudosymmetry is not so "pseudo" after all.
If this subject interests you, I recommend Motulsky Intuitive Biostatistics: A Nonmathematical Guide to Statistical Thinking that will provide you a strong quantitative foundation to evaluate any hypothesis. I also liked Greenhalgh How to Read a Paper: The Basics of Evidence-based Medicine and Stanovich formidable What Intelligence Tests Miss: The Psychology of Rational Thought. Both books explore various facets of Seethaler's critical thinking in greater details.