I am continuing to play with R. I am looking at older data measured and recorded in a different way.
I am (re-)reading Jaynes “Probability”. My first reading was difficult. It seems better the second time.
I post this as prompted by Jaynes’fondness for “desiderata” ( and in the spirit of Star Trek’s50 th anniversary):
I recently finished reading the ebook formats of the above. I am still getting used to this medium.
I found both these books refreshing. The flow of information is increasing in volume and complexity with every passing day. “Big data” is the catch-phrase in many domains. “Weapons of Math Destruction” aims to highlight the limitations and potential unintended (and perhaps intended in some situations) adverse consequences on vulnerable people (on a large scale and leaving people without recourse to correction).
This is not an anti-science book. On the contrary, it is clarion call to data scientists, end-users and people to increase communication and understanding of what models and learning algorithms can and cannot do. The author stresses the importance of iterative refinement and the need to incorporate measures of societal and other less tangible outcomes.
Daniel Levitin’s book was a wonderful companion. This is a very useful and readable guide (and exhortation) to critical thinking when presented political, business and journalist claims. The first part of the book discusses statistical aspects. The author provides numerous examples and visual aids. The importance of critical reasoning and taking the time to practice and learn these skills that we are are not ‘hard-wired’ for (as in Kahneman’s Thinking Fast and Slow, there are a number of references to the work of Tversky and Kahneman in the book).
I think both books are timely. In tandem with the explosion of “big data”, computational power, and increasingly complex statistical computing and machine learning, there is increasing momentum to deal with “bad science” (conduct, methodology, reporting and dissemination into the public arena). Asimov’s quotation (used in the Levitin book) seems apt:
“The saddest aspect of life right now is that science gathers knowledge faster than society gathers wisdom.”
The world faces many complex challenges and there does appear to be an “anti-science” voice emerging (and perhaps inward looking fear and intolerance). These two books (in different ways) help to point us to the path of wisdom to deal with the complex challenges.
Nothing in life is to be feared, it is only to be understood. Now is the time to understand more, so that we may fear less.- Marie Curie
Some xkcd brilliance and other amusements:
I have come across another jewel in the firmanent. There has been an increasing recognition of the prevalence of reliance on p-values and other related issues of statistical rigor in conduct and reporting in, particularly, biomedical science.
Professor McElreath provides an excellent lecture series to complement his book. There are a number of resources made available. Perhaps, it may not be relevant to all disciplines. Any steps towards a more thoughtful and critical appraisal of knowledge and our interpretations and inferences should be applauded. I believe this is such an endeavour. This has never been more important as “big data” increasingly interacts with our lives.
I was looking through my bookshelf when I came across this book. I had not read it!
The book is ‘old’. However, the delightfully humorous and clear lessons to us remain relevant (and perhaps are even needed more now than ever). The newspaper was a wonderful launching pad for these explorations.
This is another post motivated by a Mathematica Stackexchange post adapting code by user halmir (visualization of a sample of the consecutive decimal representation). The following is visualization of rational which are either finite or recurring).