Basis Lab

Counting Without Listing

Counting Turns Into Chance

Last timePutting It Back, or Not

A probability is a count divided by a count. The division is easy; the work is making sure both halves count the same kind of thing and that the outcomes really are equally likely.

Four lessons of counting have produced numbers with no use yet. This lesson

gives them one, and it takes a single line to state.

FIG 1A probability, when the outcomes are equally likely
the thing described, such as the hand being a flush or the two dice adding to seven
the length of the full list of possibilities, which is the count the previous lessons produce
how many entries of that same list match the description. It must be counted from the same list, which is the trap of this lesson
a number between nought and one. Nought means it never happens and one means it always does, and both of those come out of the formula rather than being added as rules
This is the whole of classical probability, and it is a fraction of two counts. The reason it needs four lessons of preparation is that both counts are usually hard and the fraction is easy. The reason it needs the rest of this lesson is that the formula is true only when the outcomes are equally likely, and that condition is not visible anywhere in the formula itself, which is exactly why it gets forgotten.

The assumption that is not written down

The formula divides by the total, which treats every outcome in the list as

carrying the same weight. Sometimes that is justified and sometimes it is

nonsense.

It is justified for a shuffled deck, a fair die, a fair coin, or a hash

function doing its job, and the justification is always symmetry: there is no

feature of the object that distinguishes one outcome from another, so they

cannot have different chances.

It is nonsense for most things observed in the world. The possible delays of

your train are a finite list, and counting them and dividing by their number

would tell you that an hour late is as likely as on time. The list being finite

is not the issue. The outcomes having equal weight is, and no amount of

careful counting repairs it.

So the question to ask before using the formula is whether anything about the

situation makes one outcome different from another. When the answer is yes, the

fraction is not a probability, and what is needed is measurement rather than

counting, which is where the course on samples picks the problem up.

Both halves, the same list

Here is the error that catches everybody once.

The lesson stops here

3 more paragraphs to go

You have read the opening. The rest of the argument, the problems that check whether it landed, and the lines worth keeping at the end all come with a plan.

The first lesson of every course in the library reads the whole way through, free, so you can see exactly what the rest of them are.

See the planThe contents

This is the reading half

Starting the course gives you your own copy of it. Every idea on every page has problems standing under it, marked with a reason rather than a tick, and any sentence you do not believe can be opened and argued with. None of that can happen on a page nobody owns.

The contents

The rest of this course

  1. 01One Choice After Another
  2. 02Putting Things in Orderopening only
  3. 03When Order Does Not Matteropening only
  4. 04Putting It Back, or Notopening only
  5. 05Counting Turns Into Chanceyou are here
  6. 06Counting the Same Thing Twiceopening only
  7. 07More Things Than Placesopening only
  8. 08When Counting Explodesopening only

Read alongside