Simple probability question

In summary: So: P(3,0,0) = 1/27 but P(1,1,1) = 6/27so your answer is 1/9, not 3/10. So it looks like the issue is that you are not considering all the possible outcomes and their respective probabilities. In summary, the probability of drawing three candies of the same kind from a jar with three varieties of candies, with replacement, is 1/9. This can be calculated by taking the product of the probabilities for each draw, each
  • #1
tramp
6
0
I got lost with simple probability question.
There are three varaeties of candies in a can.
Three candies are selected randomly.
What is the probability that all of them are of the same kind?

It seems to be [itex]1\frac{1}{3}\frac{1}{3}=\frac{1}{9}[/itex]

But at the same time we can calculate it as [itex]\frac{C^1_3}{C^3_{3+3-1}}=\frac{3}{10}[/itex]

What is the right answer here?
 
Physics news on Phys.org
  • #2
tramp said:
I got lost with simple probability question.
There are three varaeties of candies in a can.
Three candies are selected randomly.
What is the probability that all of them are of the same kind?

It seems to be [itex]1\frac{1}{3}\frac{1}{3}=\frac{1}{9}[/itex]

But at the same time we can calculate it as [itex]\frac{C^1_3}{C^3_{3+3-1}}=\frac{3}{10}[/itex]

What is the right answer here?

You didn't specify the proportion of the three kinds of candies in the can. You can estimate that by sampling with replacement, but that's a different question. For this question let's say each of the three kinds are equal in number. Let [itex]n_i[/itex] be the number of each kind and the total [itex] N=\sum_{i=1}^{i=3}[/itex]

The first draw determines the target kind and is drawn with probability one. What is the probability of the same kind at the next draw without replacement? If you've drawn the same kind on the second draw, what is the probability of drawing the same kind on the third draw without replacement?

It's clear that if you draw with replacement, the probability is 1/9. so your calculation cannot be correct for drawing without replacement.
 
  • #3
Thank you for response.
Let say candies are at the same proportion and this is draw with replacement (we return candy to the can after every draw).

The issue is that if I try to calculate number of possible outcomes I get

[itex]C_{3+3-1}^3=10[/itex]

We can enumerate them as

v1 | v2 | v3
0 0 3
0 1 2
0 2 1
0 3 0
1 2 0
2 1 0
3 0 0
2 0 1
1 0 2
1 1 1

Each outcome is equally likely so based on this enumeration probability is [itex]\frac{3}{10}[/itex]

I expect it to be [itex]\frac{1}{9}[/itex]

This is stupid but I do not see where I am wrong here :-(.
 
  • #4
tramp said:
Thank you for response.
Let say candies are at the same proportion and this is draw with replacement (we return candy to the can after every draw).

The issue is that if I try to calculate number of possible outcomes I get

[itex]C_{3+3-1}^3=10[/itex]

We can enumerate them as

v1 | v2 | v3
0 0 3
0 1 2
0 2 1
0 3 0
1 2 0
2 1 0
3 0 0
2 0 1
1 0 2
1 1 1

Each outcome is equally likely so based on this enumeration probability is [itex]\frac{3}{10}[/itex]

I expect it to be [itex]\frac{1}{9}[/itex]

This is stupid but I do not see where I am wrong here :-(.

Well, first the 'with replacement' problem is not very interesting or practical. Who takes candy from a jar just to put it back? However if you happen to get your favorite flavor with the first draw, it might be interesting know what the probabilities of getting more like that.

You are dealing with only two columns, not three. The first draw simply establishes the "target". The draws are independent, so it's simply 1/3 probability for each of the remaining draws. To get the target flavor twice in a row would simply be the product or 1/9. If you started with a preconceived choice of flavor, then the probability of getting three in a row of that flavor is of course 1/27 with replacement.

However without replacement you need to adjust the denominator for the items removed. If you are only interested in getting three in a row after establishing your target with the first draw, you must calculate the new proportion for the second and third draw given your series is intact.:

[itex] P_2 = n_i - 1/N - 1;, P_3 = n_i -2/N - 2[/itex] I don't see this as a combinatorial problem. The product of P2 and P3 is your answer since P1=1.

EDIT: You would use a combinatorial approach if you asked about how many ways you can draw n things from N things in a non contingent context If you want to ask that question, you need to re post.
 
Last edited:
  • #5
tramp said:
Thank you for response.
Let say candies are at the same proportion and this is draw with replacement (we return candy to the can after every draw).

The issue is that if I try to calculate number of possible outcomes I get

[itex]C_{3+3-1}^3=10[/itex]

We can enumerate them as

v1 | v2 | v3
0 0 3
0 1 2
0 2 1
0 3 0
1 2 0
2 1 0
3 0 0
2 0 1
1 0 2
1 1 1

Each outcome is equally likely so based on this enumeration probability is [itex]\frac{3}{10}[/itex]

I expect it to be [itex]\frac{1}{9}[/itex]

This is stupid but I do not see where I am wrong here :-(.
Each outcome is NOT equally likely when listed as above.

P(3,0,0) = (1/3)^3

P(1,1,1) = 6 x (1/3)^3
 
  • #6
Well, first the with replacement problem is not very interesting or practical. Who takes candy from a jar just to put it back? However if you happen to get your favorite flavor with the first draw, it might be interesting know what the probabilities of getting more like that.

Well, I can re-frase same problem in 100 different ways. Let say we are talking about three guys randomly selecting from three targets to shoot to. Does it make it more interesting? :-). I would say exactly the oposite. Same problem without replacement it totally trivial and not interesting.

You are dealing with only two columns, not three. The first draw simply establishes the "target". The draws are independent, so it's simply 1/3 probability for each of the remaining draws. To get the target flavor twice in a row would simply be the product or 1/9. If you started with a preconceived choice of flavor, then the probability of getting three in a row of that flavor is of course 1/27 with replacement.

I totally agree, that is why in my first post I said that it seems to be [itex] 1\frac{1}{3}\frac{1}{3} [/itex].
However, in this case we have finite number of equally likely outcomes (unless you can see why they are not equally likely).
As such we can calculate probability as [itex]\frac{\text{number of favorable outcomes}}{\text{number of possible outcomes}} [/itex]

So we should be able to tackle same problem from combinatorial prospective.

The issue is that the answer I am getting using this approach is [itex]\frac{3}{10}[/itex].

So I am trying to figure out what I am doing wrong.
 
Last edited:
  • #7
Each outcome is NOT equally likely when listed as above.

P(3,0,0) = (1/3)^3

P(1,1,1) = 6 x (1/3)^3

Thanks awkward.

Finally I got it. I thought I am totally crazy :-).

[itex] p(1,1,1) = 1(1-\frac{1}{3})(1-\frac{2}{3}) =\frac{2}{9} [/itex]
 

1. What is simple probability?

Simple probability is a measure of the likelihood that an event will occur, expressed as a number between 0 and 1. A probability of 0 indicates that the event will definitely not happen, while a probability of 1 indicates that the event will definitely occur.

2. How do you calculate simple probability?

To calculate simple probability, you divide the number of favorable outcomes by the total number of possible outcomes. For example, if you flip a coin, there are two possible outcomes (heads or tails) and one favorable outcome (heads). So the probability of getting heads is 1/2 or 0.5.

3. What is the difference between independent and dependent events in simple probability?

In simple probability, independent events are those where the outcome of one event does not affect the outcome of another event. For example, if you roll a die twice, the outcome of the first roll does not affect the outcome of the second roll. In contrast, dependent events are those where the outcome of one event does affect the outcome of another event. For example, if you draw a card from a deck and then draw another card without replacing the first one, the second draw is dependent on the first.

4. How do you determine if events are mutually exclusive in simple probability?

Events are mutually exclusive if they cannot occur at the same time. In simple probability, this means that the probability of both events occurring is 0. For example, if you draw a card from a deck and then draw another card without replacing the first one, the two events of drawing a red card and drawing a black card are mutually exclusive.

5. What is the difference between theoretical and experimental probability?

Theoretical probability is based on mathematical calculations and assumes that all outcomes are equally likely. Experimental probability is based on actual observations and may differ from theoretical probability due to chance or other factors. For example, the theoretical probability of rolling a 6 on a fair die is 1/6, but in an experiment, you may roll a 6 more or less frequently than 1/6 due to random chance.

Similar threads

  • Set Theory, Logic, Probability, Statistics
Replies
2
Views
1K
  • Set Theory, Logic, Probability, Statistics
Replies
1
Views
1K
  • Set Theory, Logic, Probability, Statistics
2
Replies
36
Views
3K
  • Set Theory, Logic, Probability, Statistics
Replies
17
Views
850
  • Set Theory, Logic, Probability, Statistics
Replies
10
Views
814
  • Set Theory, Logic, Probability, Statistics
Replies
5
Views
1K
  • Set Theory, Logic, Probability, Statistics
Replies
2
Views
1K
  • Set Theory, Logic, Probability, Statistics
Replies
5
Views
895
  • Set Theory, Logic, Probability, Statistics
Replies
3
Views
1K
  • Set Theory, Logic, Probability, Statistics
Replies
6
Views
1K
Back
Top