Acknowledgments: many examples taken from the book Intuitive Biostatistics,4th edition
2025-10-01
Understand once and for all that statistics and probability are NOT intuitive
Definitions, terminology & notations
Next week:
Foundational concepts: random trials, exclusive and non-exclusive outcomes, probability rules
Probability distributions and sampling distributions
Motivation
We almost never sample an entire population. So we can’t nail down parameters from populations.
But we can make educated guesses of parameters by making estimates from samples.
We know that estimates will differ from parameters by chance.
So, we must incorporate uncertainty in our estimation.
How can we rigorously quantify this uncertainty?
“If something has a 50% chance of happening, then 9 times out of 10 it will” — Yogi Berra
“easy to understand”
“instinctive, or acting on what one feels to be true even without reason”
Do you spot any patterns?
Pick a range that you think has a 90% chance of containing the right answer
Don’t consult anything/anyone. The goal is to quantify your uncertainty. If you truly have no idea, you can use the broadest range that is plausible (which you can be 100% sure includes the answer) but try to narrow down your answers to a range that you are 90% sure contains the right answer.
These questions were used in a study by Russo and Shoemaker (1989) and 99% of \(~1,000\) participants, but most of them included narrow ranges that included 30 to 60% of correct answers.
Similar studies done with experts answering questions in their own field of expertise led to similar results.
From: makeameme.org
B21: Biostatistics with R