How Not to be Wrong - Jordan Ellenberg (Book Read May 2020)

I have had this book for a few years.  The COVID-19 school closure period allowed me a lot of time to read and I am glad to finally finish this book.

Part I - Linearity:  
-In the opening chapters, the author introduces the concepts of limits and made connections to linear regression.  
-"Not all curves are straight lines" is a reason why we should be careful in making predictions.
-Smaller sample sizes have more variability.
-Don't misinterpret the Law of Large Number with events that should be independent.
-Don't use proportions when numbers are more meaningful.

Part II - Inference
-Pitfalls of using probability
-Lottery in Massachusetts
-Buffon's Needle Problem

Part III - Expectation
-Miss more planes
-Math theories

Part IV - Regression
-The voting system
-Lung cancer makes you smoke

Part V
-The joy of doing math