Simple conditional probability question

In summary, conditional probability is the likelihood of an event occurring given that another event has already occurred. It is calculated by dividing the probability of the joint occurrence of both events by the probability of the first event occurring. The difference between conditional and unconditional probability is that conditional probability takes into account a specific condition or event that has already occurred. It cannot be greater than 1 as it represents the likelihood of an event occurring given that another event has already occurred. In real life, conditional probability is used to make predictions and decisions based on known information, such as in medicine to determine the likelihood of a patient having a certain disease.
  • #1
bradyj7
122
0
Hello,

I'm trying to work out a conditional probability.

I have hundreds of measurements of two variables (1) Start Time and (2) Journey time.

I've created a frequency table.

https://dl.dropbox.com/u/54057365/All/forum.JPG

How can I work out the Journey time given a start time?

P(JT | ST) = P(JT n ST)/P(ST)

How would you work out these?

For example given 8am what would be the probable journey time?

Thanks for your help

John
 
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  • #2
Essentially each row is P(JT|ST). Divide each entry by the total number for the row.

If the JT is supposed to be continuous, then graph each row with some curve fit and normalize so the integral = 1 to get the probability density.
 
  • #3
As mathman says, the short answer is to divide the frequency for a start time, journey time combination by the total for that start time. To do better, you need a mathematical model for the relationship, and best of all is to base that model on knowledge of the physical system.
In the present case, I would assume that the rate of progress of the journey depends on time of day. This will consist of a deterministic term r(t) and a probability distribution with zero mean. You can assume the basic shape of the distribution is fixed, but the variance will also be a function of time.
Next, find the values of r(t), at one minute steps say, which give the best fit to your data. Plot that up and find a reasonable curve to fit it. Finally, look at the error term and figure out how the variance changes with time of day. Then see if you can find a standard distribution to model it.
 

Related to Simple conditional probability question

1. What is conditional probability?

Conditional probability is the likelihood of an event occurring given that another event has already occurred. It is usually denoted as P(A|B), where A represents the event we are interested in and B represents the event that has already occurred.

2. How is conditional probability calculated?

Conditional probability is calculated by dividing the probability of the joint occurrence of both events (P(A ∩ B)) by the probability of the first event occurring (P(B)). This can be represented as P(A|B) = P(A ∩ B) / P(B).

3. What is the difference between conditional and unconditional probability?

Unconditional probability, also known as marginal probability, is the likelihood of an event occurring without any prior knowledge or conditions. On the other hand, conditional probability takes into account a specific condition or event that has already occurred.

4. Can conditional probability be greater than 1?

No, conditional probability cannot be greater than 1. This is because it represents the likelihood of an event occurring given that another event has already occurred, so it cannot be more than 100%.

5. How is conditional probability used in real life?

Conditional probability is used in real life to make predictions and decisions based on known information. For example, in medicine, doctors may use conditional probability to determine the likelihood of a patient having a certain disease based on their symptoms and medical history.

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