**Audio-book Review****By Chet Yarbrough**

(Blog:awalkingdelight)

Website: chetyarbrough.blog

**How Not to Be Wrong**

**By: Jordan Ellenberg **

**Narrated by Jordan Ellenberg**

Jordan Ellenberg (Author, American mathematician, Professor of mathematics at University of Wisconsin-Madison).

Like listening to Brian Greene (a theoretical physicist), Jordan Ellenberg reminds one of what it must be like to be the smartest person in the room. One feels better from the experience of listening to “How Not to Be Wrong”, but understanding will be a struggle for most non-mathematicians. A non-mathematician leaves Ellenberg’s book better informed, if not entirely enlightened.

A non-mathematician may be hesitant to take Ellenberg’s book in hand. Ellenberg does not convince one that mathematics will always help one “…Not…Be Wrong”. However, Ellenberg convincingly argues mathematics will offer a better chance of being right.

Ellenberg is a professor of mathematics. He capsulizes mathematics as the language of science. He reveals how mathematics offers a qualified understanding of reality.

It is impossible to deny the validity of Ellenberg’s claim that mathematics is the language of science.

It is difficult to conceive of truth without mathematics because it provides a basis for repeatable experimental results. However, we live in a world of probabilities according to quantum mechanics. That implies mathematics cannot be the sole determinate of truth.

Ellenberg shows how “right” is qualified by mathematical proof. Like Brian Greene, Ellenberg shows how mathematics brings one closer to truth but only to the point of a “null hypothesis”. A null hypothesis is a repeatable experiment where there is zero (null) difference in results. Being right is dependent upon the same results from population samplings and relevant repeatable experiments.

What strikes at the heart of Ellenberg’s explanation of “How Not to Be Wrong” is human natures tendency to make events conform to plan. Human beings can lie to themselves.

Lying to oneself is the source of conspiracy theories based on the human strength and weakness of seeing patterns in nature. Perceived patterns from observation may or may not meet the criteria of a “null hypothesis”. Ellenberg suggests one should be skeptical of observed patterns that defy common sense.

What is disturbing about Ellenberg’s explanation of “How Not to Be Wrong” is that probability enters into the equation of truth.

This is the same fundamental law noted by theoretical physicists like Brian Greene. With the use of mathematics as the language of science, one can only expect a probability of truth: not certainty.

Ellenberg notes one must keep in mind–not being wrong is entirely different from being right. Determination of whether one is right or wrong is two-edged where one edge offers a probability of being right while the other implies possibility of being wrong. The uncertainty of probability is a lighted match that can burn down a forest of science.

That match is fanned into a flame by those who disparage all of science because of revised theories based on newly discovered facts. As an example–our recent experience with the former President of the United States who discredited the science of masking and distancing during the Covid 19 pandemic.

Ellenberg gives numerous examples of people who are misled by population sampling and the concept of correlation. Human nature often misleads people to see patterns where cause is unrelated to effect. Ellenberg argues that better understanding of mathematics can teach humans “How Not to Be Wrong”.

Being right is always qualified by some level of probability. Ellenberg explains repeatable experiment, with a level of consistency in mathematical proofs, is our way of not being wrong. Good to know, but daunting to achieve when mathematics is the only avenue for understanding.

Don’t we all want to know “How Not to Be Wrong”? Is the language of mathematics the only avenue for understanding? Therein lies the fear of realizing you are not the smartest person in the room.