Simple conditional probability question

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SUMMARY

This discussion focuses on calculating conditional probability, specifically P(JT | ST), where JT represents Journey Time and ST represents Start Time. The user, John, seeks to determine probable journey times based on start times using a frequency table. The solution involves dividing the frequency of journey time and start time combinations by the total for the respective start time. For continuous journey times, it is recommended to graph the data, apply a curve fit, and normalize the results to achieve a probability density function.

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  • Understanding of conditional probability and its notation (e.g., P(JT | ST))
  • Familiarity with frequency tables and data normalization techniques
  • Basic knowledge of statistical modeling and curve fitting
  • Experience with probability distributions and their properties
NEXT STEPS
  • Learn about statistical modeling techniques for time series data
  • Explore methods for curve fitting and normalization in data analysis
  • Study probability density functions and their applications in continuous data
  • Investigate the impact of time of day on journey time variance and distribution
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Data analysts, statisticians, and researchers interested in conditional probability and statistical modeling of journey times based on start times.

bradyj7
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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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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.
 
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.
 

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