I’m away to a conference this week, and so thought it would be fun to start a lecture series Understanding Statistics and Probability (this is posting automatically—I’ll be answering all questions by Monday, 12 October). They’ll be a series of brief chats about the meaning of statistical concepts. We’ll try and keep away from any formulas and concentrate on ideas. I’m aiming for 12-15 minutes for each lecture. Look for these every Friday.
I’ll be roughly following my class notes, which are linked to the left—the book Breaking the Law of Averages.
Feel free to ask questions. I never use canned examples—nobody ever remembers a canned example—so I’ll be relying on you, my faithful readers, to supply situations, and maybe even data.
All knowledge is conditional on evidence which follows a chain that least ultimately back to our intuitions. There are many things we know are true based on no evidence except that of our intuition. Another way to say this, is that our beliefs, all of them, are eventually grounded in faith. This is true for everybody.
While all knowledge is conditional, not all the information leads to certainty. Some propositions are thus known uncertainly. We use probability to quantify this uncertainty. Because of this, all probability, like all knowledge, is conditional. Probability, therefore, is a matter of logic, and we have to understand some basic steps in logic before we can go further. We’ll do that next week.