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Chapter 13 · Probability

Being told one event happened shrinks the sample space you count against

Probability after you learn something14 min

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14 min.

The idea

Nothing about the coins changes when somebody tells you the first one came up tails. What changes is the list you are allowed to count against. The chapter builds its whole definition out of that single move on Part II pp. 406–408: keep only the outcomes that agree with what you were told, and the favourable ones among those are exactly the outcomes the two events already shared. The formula that ends up labelled Definition 1 is not a new axiom, it is that count divided top and bottom by the size of the original space, and a student who watches the division happen never afterwards has to remember which probability goes underneath.

What you should be able to do

  • Describe in one sentence what being told that an event has happened does to the list of outcomes still in play
  • Reproduce the chapter's three-coin argument, naming the two events and the four outcomes each contains
  • Explain why the outcomes that stay favourable are precisely those in the intersection of the two events
  • Write the conditional probability as a ratio of two counts, and then as a ratio of two probabilities, and show that the second follows from the first
  • State Definition 1 with its side condition, and say what goes wrong without it
  • Read the vertical bar correctly: name which event supplies the new ground and which one is being measured
  • Compute both conditionals of a given pair and show that they are in general different numbers
  • Apply the definition where the outcomes are not equally likely, using probabilities of outcomes rather than a head count
  • Read a tree diagram of a two-stage experiment and recover the outcome list from it

Words to know

TermDefinition in one lineFirst introduced
conditional probabilitythe chance of one event worked out on the smaller list of outcomes that a second event leaves standingprinted in this chapter, italicised at first use (§13.2, Part II p. 407) and set down as Definition 1 (Part II p. 408)
sample spacethe full list of outcomes an experiment can produceprinted in this chapter (§13.2, Part II p. 406)
random experimenta trial whose outcome is not settled in advanceprinted in this chapter (§13.1 and Definition 1, Part II pp. 406, 408)
elementary eventa single outcome of the experiment, treated as an event on its ownprinted in this chapter (§13.2, Part II p. 408)
equally likelysaid of outcomes the experiment gives no reason to separateprinted in this chapter (§13.1 and §13.2, Part II pp. 406, 412)
tree diagramthe branching drawing of a staged experiment, one level per stageprinted in this chapter, in quotation marks at Example 7 (Part II p. 412)
axiomatic approachthe treatment of probability as a function on events obeying stated rulesprinted in this chapter, but named as earlier learning rather than taught here (§13.1, Part II p. 406)
reduced sample spacethe shorter outcome list you count against once you know the given event happenedan added compound; this chapter describes the shrinking on Part II p. 407 and never gives it a name
conditioning eventthe event on the right of the bar, the one that supplies the new groundan added label; the chapter has no term for this role
joint probabilitythe chance that both events happen, the quantity on top of the fractionan added vocabulary; not printed in this chapter, which writes only the intersection
base ratethe unconditional chance of the event, before any information arrivesan added term, not printed anywhere in this chapter

Where people slip up

  • "Conditioning changes the coins." It changes nothing physical. The coins have already landed. What the information changes is which outcomes you are entitled to count, which is a statement about your list, not about the world.
  • "The probability of the first given the second is the same as the second given the first." They share a numerator and have different denominators, so they agree only when the two events have equal probability. Exercise 13.1 Q1 makes them two thirds and one third on the same three inputs; show both together.
  • "Divide by the probability of the event you want." Divide by the event you were told about. Deriving the formula from the head count fixes this permanently, because in the count form the denominator is visibly the list you are standing in.
  • "The condition on the denominator is a technicality." It is the difference between an answer and no answer. Exercise 13.1 Q16 exists to make a student write not defined rather than nought.
  • "Conditional probability is a smaller probability." It can be larger, smaller or equal. In Example 5 it equals the unconditional chance; in Example 2 it is smaller; conditioning on a rarer event can push it up. Show one of each.
  • "Both children being boys, given one is a boy, is one half." The famous one. There are three surviving pairs, not two, because a girl-then-boy family and a boy-then-girl family are different outcomes and both qualify. The chapter lists all four pairs on Part II p. 410 for exactly this reason.
  • "Once outcomes stop being equally likely, the whole method fails." Only the head-counting fails. Example 7 runs the same definition on a space where the outcomes carry two different probabilities.
  • "Every branch label on a tree is a branch chance." Not in this chapter's own drawing. Fig 13.2 labels its second level with leaf probabilities. Say so when the figure is shown, or a student will multiply along the path and get a wrong number that looks right.
Transcript2,107 words

Here is the only question this whole topic is built on. You are about to bet on something. Somebody tells you that a different thing has already happened. Should that change your bet? Sometimes it should, sometimes it should not, and the point of the next twenty minutes is that there is a single mechanical answer to when and by how much. And I want to say at the start what the mechanism is not. Nothing physical changes. The coins have already landed. Nobody moves them.

What changes is the list of outcomes you are entitled to count. That is a statement about your information, not about the world, and every formula in this topic is bookkeeping on top of it. Three fair coins on the table. Eight outcomes, and because the coins are fair each one carries a chance of one eighth. Two events matter here. The first is that at least two heads show. That holds four of the eight outcomes: three heads, or heads heads tails, or heads tails heads, or tails heads heads.

The second is that the first coin shows tails. That also holds four: tails heads heads, tails heads tails, tails tails heads, tails tails tails. Four out of eight each, so each has a chance of one half. And they share exactly one outcome between them — tails, then heads, then heads — so the chance that both happen is one eighth. Those three numbers are the whole of the arithmetic. Everything from here is about which of them goes where.

Now somebody tells you the first coin came up tails. Four of the eight outcomes contradict that, and they are gone. Not unlikely. Gone. Heads heads heads cannot be the truth if the first coin is tails. What is left is four outcomes, and you are allowed to treat that shorter list as a fresh experiment in its own right. That sentence is the entire idea of this topic, and everything after it is arithmetic.

I am going to call the shorter list the reduced sample space. That is my name for it, not a standard one, but it is worth having a name for the thing that does all the work. So: among those four survivors, how many still give you at least two heads? One. Tails heads heads. The other three survivors have at most one head between them. And look at which outcome that is. It is the one both events already contained. That is not a coincidence about coins.

To be favourable now, an outcome has to do two things. It has to agree with what you were told, or it is not on the list at all. And it has to be in the event you are asking about, or it is not favourable. Both conditions at once is exactly what the intersection of the two events means. So the favourable survivors are the shared outcomes, always, with no further argument.

Which gives the answer straight away, as a ratio of two head counts. One favourable survivor. Four survivors. One in four. Compare that with the chance of at least two heads before anybody told you anything, which was one half. The information has halved it. Notice what is underneath that fraction. It is the number of outcomes in the event you were told about. You are standing inside that event and counting; there is nowhere else to count from.

If you remember nothing else from this video, remember the shape of that fraction, because in a minute it will be written with probabilities instead of counts and the denominator will look arbitrary. It is not. It is the list you are standing in. Now one small piece of bookkeeping, and it takes three seconds. Divide the top of that fraction by eight, and the bottom by eight. The value cannot change; that is what dividing both parts means.

The top was one outcome. One over eight is the chance of both events happening — the shared eighth we worked out earlier. The bottom was four outcomes. Four over eight is one half, which is the chance of the event you were told about. So the same answer, one quarter, is now written as a chance of both, divided by a chance of the one you were told about. And you watched the division happen, so you never have to memorise which one goes underneath.

That is the definition, and it is the first thing here that gets set down formally. The probability of one event given another is the probability that both happen, divided by the probability of the one you were given. There is a condition attached, and it is not decoration. The probability underneath must not be nought. Two things go wrong at once if it is. The obvious one is that you would be dividing by nought. The real one is that an event of probability nought leaves you no reduced list at all. There is nothing to stand inside and count.

So the answer there is not nought. It is not defined. There is a standard exercise item whose entire purpose is to make you write those two words instead of a number, and people still write nought. A word about the notation, because it is read wrongly more often than any other symbol here. The vertical bar has two sides and they do completely different jobs. On the right of the bar is the ground — the thing you were told, the event that shrank the list. On the left is what you are measuring on that ground.

Read it aloud as: the chance of the left-hand thing, given the right-hand thing. Given. Told. Standing on. And the rule that follows is the one everybody gets backwards. You divide by the probability of the event on the right. Not the one you are asking about. The one you were told. If you ever lose it, go back to the counts. In the count form the denominator is visibly the list you are standing in, and no amount of forgetting can move it.

So what happens if you turn the bar around? You get a different number. In general, a completely different number. Here is a pair that makes it unmissable. One event has probability six tenths, the other three tenths, and the chance that both happen is two tenths. Two tenths over three tenths is two thirds. Two tenths over six tenths is one third. Same shared part on top; different ground underneath; twice the answer one way round.

They agree only when the two events are equally likely, because then the two denominators are the same number. And that is not a guess. I ran every pair of events you can build out of the three-coin experiment — nearly fifty nine thousand ordered pairs that share at least one outcome — and the two conditionals agree at eleven thousand seven hundred and sixty three of them. The pairs where they agree and the pairs that are equally likely are the same pairs. Not one exception.

Five shapes of the same move, quickly, because the mechanism never changes and only the list does. Two children. Four ordered outcomes: boy boy, boy girl, girl boy, girl girl. Told that at least one is a boy, three survive, and one of those three is two boys. One third. Most people say one half before they see the list, because they think of boy girl and girl boy as one case. They are two outcomes, and both survive, which is why the answer is a third.

Ten numbered cards. Told the number is over three, seven survive. Four of those seven are even. Four sevenths — and notice that is bigger than the plain chance of an even card, which was one half. Conditioning does not always shrink things. A school of a thousand with four hundred and thirty girls, a tenth of whom are in the twelfth year. The chance of a girl is nought point four three, the chance of a twelfth year girl is nought point nought four three, and dividing gives nought point one. Which is the tenth you were handed at the start, arriving back unchanged. That makes it an excellent check and a terrible puzzle.

A die thrown three times, two hundred and sixteen outcomes. Told the first two throws were a six and a five, six outcomes survive, and one of them has a four on the third throw. One sixth — which is exactly the chance of a four on one throw. The information changed nothing at all, and that is the first hint of independence. A die thrown twice, told the two faces add to six. Five outcomes survive; two of them contain a four. Two fifths. Without the information, the chance a four shows at all was eleven thirty sixths.

Now the case that separates the two forms of the formula, and it is the reason the definition is written in probabilities rather than in counts. Toss a coin. If it comes up heads, toss it again. If it comes up tails, throw a die instead. Eight outcomes. But they are not equally likely. The two head outcomes carry a quarter each. The six tail outcomes carry a twelfth each. A quarter and a quarter and six twelfths is one, so it is a proper sample space.

Now: at least one tail appears — that is three quarters. The die shows a number bigger than four — that is two outcomes, a twelfth each, one sixth. And those two outcomes are also the only ones the two events share. So the conditional is one sixth divided by three quarters, which is two ninths. Try it by counting instead. Seven outcomes survive, two of them are favourable, two sevenths. That is wrong. Two sevenths is not two ninths.

The head count assumed every survivor was as likely as every other, and here they are not. The definition never assumed it. That is what the probability form buys you, and it is why it is the one that gets written down. That two stage experiment is usually drawn as a tree. One branching at the first stage, then a branching at the second, and eight leaves at the bottom.

A tree is worth drawing, because it turns a staged experiment back into a flat list of outcomes, which is the only form the definition knows how to eat. But there is a trap in how the numbers get written on it, and I have to flag it because nothing warns you. You will see this tree drawn with a half on each first level branch, and then a quarter on each head branch and a twelfth on each tail branch at the second level.

Those second level numbers are the probabilities of the whole outcomes. They are not the chances along those branches. The chance along a head branch is a half, and a half of a half is a quarter. The chance along a tail branch is a sixth, and a half of a sixth is a twelfth. So if you do the natural thing and multiply the two labels along a path, you get a half times a quarter, which is an eighth. The outcome is a quarter. You are out by a factor of two, on every single path.

The reading I have just given you is mine, and a careful reader should check it against whatever they are looking at. Multiply branch chances, never leaf probabilities — and if a label is already the answer, stop. What to keep. Being told something does not change the experiment. It changes the list of outcomes you are allowed to count against. Cross out everything that contradicts what you were told. Among what is left, the favourable ones are the outcomes both events contained.

That gives a ratio of two counts. Divide both by the size of the original list and it becomes the chance of both, over the chance of the one you were told. Divide by the event on the right of the bar. Always. And if that event has probability nought, the answer is not defined rather than nought. Turning the bar around gives a different number unless the two events are equally likely.

And the conditional can be bigger, smaller or exactly the same as the plain chance. Two boys given at least one boy went up. A four on the third throw given the first two went nowhere at all. Conditioning is not shrinking; it is recounting.

Where this fits

Either side of this one

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