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## 7th grade

### Course: 7th grade > Unit 7

Lesson 3: Compound events and sample spaces# Sample spaces for compound events

Explore the notion of a "sample space". See a sample space represented as a tree diagram, table, and list.

## Want to join the conversation?

- Can you present the information of a sample space diagram differently?

.Are the different methods of showing this information

(except from the ones shown of course)(20 votes)- Another method you can use to find the number of possible outcomes is to multiply the outcomes. For example, since there are 3 flavors and 3 different sizes you can multiply 3 x 3 which is 9, and also means that there are 9 possible outcomes.(27 votes)

- at0:35what is that box thing Sal drew(13 votes)
- Thats the space where he puts the possible outcomes(5 votes)

- "I encourage you to pause the video and work this out on your own"(12 votes)
- i don't have to the questions in the video are relatively easy LOL(1 vote)

- The probability of the first coming up a 3 is the sum was less than 7?(8 votes)
- Can't U just do 3 *3 because 3 *3 =9 . Since there is 3 options each ones of the 3 flavors(9 votes)

- How many numbers are in 6 dices combined together?(8 votes)
- If it is a four-sided dice, then there are 24 numbers. If it a six-sided dice, then there are 36 numbers.(9 votes)

- At4:29, shouldn't Sal have said, "Chocolate, Vanilla, and Strawberry?"(9 votes)
- I don't get the difference between the three. For example a + b + c = d. D is still the sum when a + c + b. Multiplication is the same. 8 * 9 * 34 = 34 * 8 * 9. Hope this makes sense.(5 votes)

- We're no strangers to love

You know the rules and so do I

A full commitment's what I'm thinking of

You wouldn't get this from any other guy

I just wanna tell you how I'm feeling

Gotta make you understand

Never gonna give you up

Never gonna let you down

Never gonna run around and desert you

Never gonna make you cry

Never gonna say goodbye

Never gonna tell a lie and hurt you

We've known each other for so long

Your heart's been aching, but

You're too shy to say it

Inside, we both know what's been going on

We know the game and we're gonna play it

And if you ask me how I'm feeling

Don't tell me you're too blind to see

Never gonna give you up

Never gonna let you down

Never gonna run around and desert you

Never gonna make you cry

Never gonna say goodbye

Never gonna tell a lie and hurt you

(Ooh, give you up)

(Ooh, give you up)

Never gonna give, never gonna give

(Give you up)

Never gonna give, never gonna give

(Give you up)

We've known each other for so long

Your heart's been aching, but

You're too shy to say it

Inside, we both know what's been going on

We know the game and we're gonna play it

I just wanna tell you how I'm feeling

Gotta make you understand

Never gonna give you up

Never gonna let you down

Never gonna run around and desert you

Never gonna make you cry

Never gonna say goodbye

Never gonna tell a lie and hurt you(6 votes) - then what is the difference between {ht,th} and {ht} in sample space for coin having? i am confused ht and th are same or different

if yes then why in above video there is not sample space for choclate small but only small choclate(3 votes)- Yes there is a difference between HT and TH in that a coin (or two coins) are being flipped

the difference can show up most easily in the question asked, for example,

What is the probability of flipping a fair coin twice and getting a heads then a tails? (1/4 because order does matter)

What the is probability of flipping a coin twice and getting one heads and one tails? (1/2 because order does not matter)

As to your second question which seems intuitive, the problem is that the sample space is created by flipping a coin twice, it just so happens that there are only two choices on a coin, so four possibilities (h first, h second)(h first, t second)(t first, h second) and (t first, t second) - the ht and th are not just interchanged, they are 2 different possibilities

The problem of small and chocolate is that the sample space is built on flavors and size, so chocolate small and small chocolate are really the same possibility rather than two distinct possibilities (he did two tree diagrams which show the 9 outcomes which just shows these are the same)

Hope this helps(5 votes)

- if any oh you are having some trouble with this try ¨probability of a compound event¨ i had trouble but after waiting this i got it. trust me it works it should be on the left of your screen on the tool bar the 4th down(5 votes)
- What would be the sample space for all the possible numbers if I were to roll 3 dice? This is on my assignment, and I'm really struggling! Would someone please provide an explanation? Thank you so much.(3 votes)
- "A sample space is the set of all possible outcomes of a statistical experiment."

Your experiment: roll 3 dice.

The outcomes:

First dice: {1,2,3,4,5,6}

Second dice: {1,2,3,4,5,6}

Third dice: {1,2,3,4,5,6}

Sample space: {(1,1,1),(1,1,2),(1,1,3),....}(4 votes)

## Video transcript

- [Voiceover] What I'm hoping
to explore in this video is the notion of a sample space. And it's a pretty, hopefully you'll find, straightforward idea. If you're doing a trial, something that is probabilistic, a trial or an experiment, a sample space is just the
set of the possible outcomes. So a very simple trial
might be a coin flip. So if you're talking about a coin flip, well then the sample space is going to be the set of all the possible outcomes. So you could get a heads or you could get a tails. That right over here is the sample space for the coin flip. And it's very useful because, for example, if these are
equally likely outcomes and you say well what's the probability of the event of a heads, you say okay that's one out of the
two equally likely outcomes. Or you could even construct, once you know all of the possible outcomes even if they aren't equally likely, you could say well let's create a
probability distribution. We at least know what the sample space is. We know what the possible outcomes are, now let's think about the probability of each of those outcomes. But a lot of times when people
talk about sample spaces, they're often, they tend to
be most useful, I would say, when you have equally likely outcomes like in the case of a fair coin flip. Because then from the sample space, it's fairly straight forward
to think about the probability of various events. But this is a simple sample
space right over here, but let's make things a
little bit more interesting. Let's imagine a world, so let's just put this aside a little bit. Let's imagine a world
where there's a bakery and at that bakery there are three types, three flavors of cupcakes, but there's also three
different sizes of cupcakes. So now we're essentially
looking at two different ways in which the thing that we're
going to be sampling can vary. So what we're doing,
let me write this down. So we have our flavors, flavors of cupcakes at this bakery. And let's say that you have chocolate, chocolate, you have, let's say there's strawberry, strawberry, and let's say that there is vanilla, there is vanilla. And they come in three different sizes. So sizes. Sizes could be small, I'll just write it out, small, medium, or large. So if you were, and let's
say each of these flavors come in each of these sizes. Or you could view it the other way around, each of these sizes come
in all three flavors. So now how do you
construct the sample space? If you were to say, look I'm gonna go, you know, I'm gonna blindfold myself and walk into this bakery and randomly somehow pickup a cupcake and my fingers can't tell the flavor or
the size of the cupcake, what are the possible,
what are the possible outcomes for the cupcake I'll pick? And the outcome would be both the flavor and the size of the cupcake. Well there's a bunch of
ways to think about this. One way is you could draw a tree. You could say, okay well I'm gonna pick three different flavors. I could either pick chocolate, chocolate, I'm gonna pick strawberry, strawberry, or I'm going to pick vanilla, vanilla. And then for each of those flavors, I'm only gonna pick a
small, medium, or large. So you could say small, medium, large. Small, so this is a small chocolate, this is a medium chocolate,
this is a large chocolate. This is a small strawberry,
medium strawberry, large strawberry. This is a small vanilla, medium vanilla, large vanilla. And so you see there's
nine possible outcomes. Once again, this is a medium chocolate. You picked a chocolate
and it was a medium one. This is a large vanilla. You picked a vanilla,
and it is a large one. And you could have done
it the other way around. You could have said, well okay, I'm going to either pick a small, medium, or large and then for each of those I'm gonna pick either a chocolate,
strawberry, or vanilla. And I'll just use the first letters. So I'm either gonna pick a chocolate, a strawberry, or a vanilla. When I write the S over
here in this magenta color, I'm talking about the flavor and if I write the S in green, I'm talking about small. So here you can have, if
you have a medium cupcake, it could be chocolate, it could be strawberry, or it could be vanilla. If you have a large cupcake it could be chocolate, strawberry, or vanilla. So for example, this was a
medium, chocolate cupcake. Over here a medium, chocolate
cupcake is this one. It's medium, chocolate. It would be that one over here. So you could use these kind of a tree diagram like this to think about the sample space, to think about the nine
possible outcomes here. But you could also, you could also do a, I guess you could say grid, where you could write the flavors, so you could have chocolate, chocolate, actually, let me just write the, well no, let me write them out. Actually, let me just, let me just write the letters since this is gonna take a long time to do. So you could have the flavors chocolate, strawberry, vanilla. So that's along that axis. And then you have your sizes. You can have a small, a medium, or large. And you can set up a grid here. So this is another way to do it. And notice this grid has nine boxes. So let's look at it. So set up the grid. Set up the grid. And so what is this one going to be? This is a small chocolate. Small. Small chocolate. Small chocolate. What is this one? This is going to be a small, a small strawberry, A small strawberry. And you could just keep
constructing like this where everything in this row,
there are all about small. Oops. Do it in the... This is small. I'm having trouble changing colors. Alright (laughing). There is a small and then this is a small, this is a small vanilla. This color changing is really, it's a difficult thing. Small vanilla. And all of these, these are all, this would be a medium chocolate. Medium strawberry. Medium vanilla. Large chocolate, large strawberry, large vanilla. And once again you have nine outcomes. This is another way to think about all of the possible outcomes when you're looking at these two ways in which my cupcakes could vary. Another way, a third way
that you could do it, is you could literally
just construct a table. Well you could say, okay I could have a chocolate, actually I'm going to
use the letters again. So let's say we make,
this is the flavor column. And then this is the size column. Size column. And so you could say I could have a chocolate that is, so let's see, there's
three types of chocolate that I could have. And they could be they could be small, medium, or large. You could say there's three types of, three types of strawberry. It could be small, medium, or large. So let me write that in. Small, medium, large. Or you could say oh, there's
three types of vanilla. There's three types of, I'm color changing again. Three types of vanilla. Once again, it could be small, medium, or large. So you have these nine possibilities. Now, sample space, the sample space isn't telling you if they're equally likely or not. It's just telling you, hey, if you're gonna do an experiment, what are all the different possibilities, the possible outcomes for that experiment? Now in the case where
they are equally likely, it can be very, very
useful because you can say you could do something like, if you said okay, it's equally likely to pick any one of these nine outcomes, you could say well what's the probability of, what's the probability of
getting something that is either small or chocolate? And so you could see well
how many of those events out of the total actually
meet that constraint? But we'll do more of
that in future videos. That's just a little bit of a clue of why we even care about things like sample spaces. Especially sample spaces like this, where we're looking along two ways or multiple ways that something can vary. And these types of sample
spaces in particular are called compound sample spaces. So these right over here, this is a compound sample space, because we're looking
at two different ways that it can vary. Not just a heads or tails, it can vary by size or by flavor. And you can even have compound sample spaces that vary
in more than two ways.