David Spiegelhalter is the Winton professor for the public understanding of statistics at the University of Cambridge. Statistics are based on probability. Here's what he said about that:
“Humans are very bad at understanding probability. Everyone finds it difficult, even I do.”
(Read the full article on Quartz.)
Last week's post was the first of this regular series of blog posts: the "Statistics Tip of the Week". There are a number of see-saws (aka "teeter-totters" or "totterboards") like this in statistics that we'll be seeing in the coming weeks and months.
Here, we see that, as the Probability of an Alpha Error goes down, the Probability of a Beta Error goes up. Likewise, as the Probability of an Alpha Error goes up, the Probability of a Beta Error goes down.
Many folks are confused about this, especially since the names for these tests themselves can be misleading. What we're calling the "2-Sample t-test" is sometimes called the "Independent Samples t-test". And what we're calling the "Paired t-test" is then called the "Dependent Samples t-test", implying that it involves more than one Sample. But that is not the case. It is more accurate -- and less confusing -- to call it the Paired t-test.
The book, Statistics from A to Z -- Confusing Concepts Clarified, will be published by Wiley on Oct. 24, 2016.
Statistics is confusing, even for smart, technically competent people. And many students and professionals find that existing books and web resources don’t give them an intuitive understanding of confusing statistical concepts. That is why this book is needed. Some of the unique qualities of this book are:
Andrew A. (Andy) Jawlik is the author of the book, Statistics from A to Z -- Confusing Concepts Clarified, published by Wiley.