Question about joint probability

On 21 of these days, ##N=1##2.2) On 39 of these days, ##N \ne 1##Therefore, out of the 40 days where ##N+S=2##, there are 18 days where ##N=1##, giving a probability of 18/40 = 0.45. Thus, the answer to the question is P(N=1|N+S=2) = 0.45.
  • #1
theone
81
0

Homework Statement



Let N denote the number of accidents occurring during one month on the northbound side of a highway and let S denote the number occurring on the southbound side. Suppose that N and S are jointly distributed as indicated in the table.

N/S 0 1 2 3+
0 0.04 0.06 0.10 0.04
1 0.10 0.18 0.08 0.03
2 0.12 0.06 0.05 0.02
3+ 0.05 0.04 0.02 0.0

Find P(N=1|N+S=2)

Homework Equations

The Attempt at a Solution


P(N=1 | N+S is not equal to 2, as in the table) = 0.10+0.18+0.08+0.03 = 0.39

I know that P(N+S) = 2 is the sum of all the different possibilities in the table where N+S=2, so 0.18 + 0.12 + 0.10 = 0.4

I do not know how to put this information together to answer the question : P(N=1 | N+S=2)
 
Last edited:
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  • #2
##P(N = 1| N +S = 2)## means the probability that ##N = 1## given that ##N+S = 2##.

So, if ##N+S = 2## what is the probability that ##N = 1##?

Or, using the frequency approach, from all the times that ##N+S = 2##, how often is ##N = 1##?

By the way, I think the first entry in your table should be ##0.04##.
 
  • #3
PeroK said:
Or, using the frequency approach, from all the times that ##N+S = 2##, how often is ##N = 1##?

would that be 1/3?

In the solution, I am seeing that the way to get P(N=1 | N+S=2) is to do P(N=1 | S=1)/P(N+S=2) = 0.18/0.40 = 0.45
but I do not understand the reason for dividing the probabilities

and the first number should be 0.04, I will edit it
 
  • #4
theone said:
would that be 1/3?

In the solution, I am seeing that the way to get P(N=1 | N+S=2) is to do P(N=1 | S=1)/P(N+S=2) = 0.18/0.40 = 0.45
but I do not understand the reason for dividing the probabilities

and the first number should be 0.04, I will edit it

I like the frequentist approach. So, let's take 100 typical days and see what happens:

1) On 40 of the days, ##N + S = 2##.

1.1) On 18 of these days, ##N = 1##

1.2) On 22 of these days, ##N \ne 1##

2) On 60 of the days, ##N + S \ne 2##

2.1) On 21 of those days, ##N = 1##.

2.2) On 39 of these days, ##N \ne 1##

In terms of these two factors, that is a complete breakdown of the numbers.

Now, when you have a conditional probability, such as in this case "given ##N + S =2##", then you are restricting your interest to those cases. Formally, this becomes your new "sample space".

In this case, we are only interest in 40 days out of every 100. (The other days we ignore. They do not matter.) What happens on those 40 days that we are interested in?

1) On 18 days out of the 40, we have ##N = 1##, that's 45% of the time.

2) On 22 days out of the 40, we have ##N \ne 1##, that's 55% of the time.

Therefore:

##P(N=1|N + S =2) = 0.45##

Does that all make sense?
 
Last edited:
  • #5
theone said:

Homework Statement



Let N denote the number of accidents occurring during one month on the northbound side of a highway and let S denote the number occurring on the southbound side. Suppose that N and S are jointly distributed as indicated in the table.

N/S 0 1 2 3+
0 0.04 0.06 0.10 0.04
1 0.10 0.18 0.08 0.03
2 0.12 0.06 0.05 0.02
3+ 0.05 0.04 0.02 0.0

Find P(N=1|N+S=2)

Homework Equations

The Attempt at a Solution


P(N=1 | N+S is not equal to 2, as in the table) = 0.10+0.18+0.08+0.03 = 0.39

I know that P(N+S) = 2 is the sum of all the different possibilities in the table where N+S=2, so 0.18 + 0.12 + 0.10 = 0.4

I do not know how to put this information together to answer the question : P(N=1 | N+S=2)

Just use the definition of conditional probability: ##P(A|B) = P(A \& B)/P(B).## So,
$$P(N=1|N+S=2) = \frac{P(N=1 \; \& \; N+S=2)}{P(N+S=2)}.$$ Can you write the event ##\{ N=1 \: \& \: N+S=2 \}## in a simpler way?
 
Last edited:
  • #6
PeroK said:
I like the frequentist approach. So, let's take 100 typical days and see what happens:

1) On 40 of the days, ##N + S = 2##.

1.1) On 18 of these days, ##N = 1##

1.2) On 22 of these days, ##N \ne 1##

2) On 60 of the days, ##N + S \ne 2##

2.1) On 21 of those days, ##N = 1##.

2.2) On 39 of these days, ##N \ne 1##

In terms of these two factors, that is a complete breakdown of the numbers.

Now, when you have a conditional probability, such as in this case "given ##N + S =2##", then you are restricting your interest to those cases. Formally, this becomes your new "sample space".

In this case, we are only interest in 40 days out of every 100. (The other days we ignore. They do not matter.) What happens on those 40 days that we are interested in?

1) On 18 days out of the 40, we have ##N = 1##, that's 45% of the time.

2) On 22 days out of the 40, we have ##N \ne 1##, that's 55% of the time.

Therefore:

##P(N=1|N + S =2) = 0.45##

Does that all make sense?

yes, it does. Thanks
So then the reason that you can't say P(N=1 | N+S=2) = (sum of the "1" row) * (sum of the "1" column) is because those two probabilities being multiplied are from a different "sample space", the one where N+S is not equal to 2 ?
Ray Vickson said:
Just use the definition of conditional probability: ##P(A|B) = P(A \& B)/P(B).## So,
$$P(N=1|N+S=2) = \frac{P(N=1 \; \& \; N+S=2)}{P(N+S=2)}.$$ Can you write the event ##\{ N=1 \: \& \: N+S=2 \}## in a simpler way?

Thanks, I think the problem is that it's hard for me to see N+S=2 and N=1 as two "events" A and B where A is conditional on B.
It feels very different than for example: A is the event of you picking a shirt from a bag of blue and red shirts, and B is the event that the shirt is a particular brand
 
  • #7
theone said:
yes, it does. Thanks
So then the reason that you can't say P(N=1 | N+S=2) = (sum of the "1" row) * (sum of the "1" column) is because those two probabilities being multiplied are from a different "sample space", the one where N+S is not equal to 2 ?

Thanks, I think the problem is that it's hard for me to see N+S=2 and N=1 as two "events" A and B where A is conditional on B.
It feels very different than for example: A is the event of you picking a shirt from a bag of blue and red shirts, and B is the event that the shirt is a particular brand

It is really very much like your shirts example, except that one attribute refers to accidents in the north lane and the other to accidents in the south lane (and for all we know, multi-vehicle accidents in both lanes at the same time).
 

1. What is joint probability?

Joint probability is a statistical measure that calculates the likelihood of two or more events occurring together. It is used to determine the probability of a specific outcome when multiple variables are involved.

2. How is joint probability different from marginal probability?

Joint probability takes into account the probability of two or more events occurring together, while marginal probability only considers the probability of a single event occurring. Marginal probability is calculated by summing up the joint probabilities of all possible outcomes for a single variable.

3. How is joint probability calculated?

Joint probability is calculated by multiplying the individual probabilities of each event. For example, if the probability of event A is 0.5 and the probability of event B is 0.3, the joint probability of both events occurring is 0.5 x 0.3 = 0.15.

4. What is the relationship between joint probability and conditional probability?

Conditional probability is the probability of an event occurring given that another event has already occurred. Joint probability is used to calculate conditional probability by dividing the joint probability of two events by the probability of the first event. This shows the likelihood of the second event occurring after the first event has already occurred.

5. How is joint probability used in real-world applications?

Joint probability is used in a variety of fields, including finance, medicine, and engineering. It can be used to predict the likelihood of certain outcomes in complex systems, such as stock market fluctuations or the success of a medical treatment. It is also used in risk assessment and decision making.

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