Statistical Science and Data Science: Don't compete; CREATE!
Category: Stats and Data Science
Statistics and Data Science have overlapping ideals, but work in very different ways.
Blog 22A: Statistics and Data Science – The Two Cultures
Building a bridge between the Statistical and Data Science professions, or perhaps recognizing that the two cultures are manifestations of the same essence.
Blog 21: Good News, Bad News, Worse News
Everyone likes to have their data analysis work result in some notable findings. Beware! "Torture the data long enough and they will confess to anything."
No. 18: Analytics, Fast and Slow
Fast to the wrong answer is not a good business or scientific strategy. Slow, but rigorous, analysis does not meet business or scientific needs either. It has to be "and."
No. 17: Analytics, Data Science and Statistics – A Rose by Any Other Name …
There is a lot of confusion over what data science is and how it is the same or different from statistics or other data analytic fields such as epidemiology or econometrics. This is my attempt to describe the "big tent" of Analytics.
No. 13: Unconsciously Biased and Consciously Unbiased
Implicit models in the back of our minds can creep into explicit models creating biased predictions that have societal implications.
No. 12: Models – Implicit and Explicit
If we fail to acknowledge that we have biases and assumptions that influence our assessment of 'objective facts,' then we delude ourselves. Our perception of reality and how we judge evidence is colored by our beliefs which arise from our specific experiences.
No. 4: We Won’t Get Fooled Again … or Will We?
What if AI in healthcare is the next asbestos?
No. 3: What Might Be
It is easy to get an answer; it is very difficult to assess the quality of that answer.
No. 2: Association, Correlation and Causation
Protect yourself from polio ... don't eat ice cream!
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