Conditional Probability vs Normal

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Discussion Overview

The discussion revolves around the application of conditional probability in determining the prevalence of a disease within a population based on prescreening results. Participants explore how to calculate probabilities using given data and clarify the relationship between conditional probabilities and overall probabilities.

Discussion Character

  • Exploratory
  • Mathematical reasoning

Main Points Raised

  • One participant questions how to calculate the probability of having the disease among the total population using conditional probability, providing specific numbers related to prescreening results.
  • Another participant agrees with the initial approach and suggests using parentheses for clarity, noting that there are two ways to have the disease based on the provided data.
  • Some participants express confusion regarding the term "Conditional" and its implications on the calculations, suggesting that the probabilities may seem straightforward despite being conditional.
  • A later reply mentions that while the probabilities can be expressed conditionally, the abundance of information makes it unnecessary to think of them strictly as conditional probabilities.
  • One participant expresses a feeling of being overwhelmed by the complexity of the topic, indicating a need for gradual learning.

Areas of Agreement / Disagreement

Participants generally agree on the approach to calculating the probabilities, but there is some uncertainty regarding the interpretation of conditional probabilities and their application in this context. The discussion does not reach a consensus on the best method to express or calculate the probabilities.

Contextual Notes

Participants mention the law of total probability as a potential method for calculation, but there is no consensus on whether this is necessary given the data provided. The discussion reflects varying levels of understanding and comfort with the concepts involved.

Who May Find This Useful

This discussion may be useful for individuals interested in understanding conditional probability, particularly in the context of medical screening and statistical reasoning. It may also benefit those who are learning about probability calculations and seeking clarification on related concepts.

jacobson00
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am a bit confused, if i want to find out for example the P(Having the disease among everyone) , using conditional, would it be total people Having the disease over total population?Prescreening Positive and Have the disease is 66
Prescreening Positive but does not the disease 150
prescreening Negative and Have the disease is 5
prescreening Negative and does not Have the disease is 555 so if using conditional probability, i want to find.P(Having the disease among everyone)

66 +5/ total population (776)

P(Prescreening Positive for everyone)

66+150/776

Am i understanding it correctly?
 
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Hi jacobson00,

Welcome to MHB! :)

I would suggest using parentheses to be more clear, but yes I agree with your approach. There are two ways of having the disease with the way the data is arranged - either you have it and you are prescreened positive or you have it and are prescreened negative. Divide by total number of people. There isn't any overlap between the groups so it seems pretty straightforward and I agree with your answer.
 
thank you. I think i was thrown off by the term "Conditional". If looks like plain probabilities.
 
jacobson00 said:
thank you. I think i was thrown off by the term "Conditional". If looks like plain probabilities.

Well they are conditional probabilities but you are given a lot of information so you don't have to think of them that way.

You could write each of these numbers as a conditional probability and calculate the answer through the law of total probability, but that's not necessary here.

$$P[+|S^{+}], P[+|S^{-}], P[-|S^{+}], P[-|S^{-}]$$
 
Phewww! i don't think i am there yet. baby steps. Thank you
 
jacobson00 said:
Phewww! i don't think i am there yet. baby steps. Thank you

Ha, it looks scarier than it is. :) Glad you found us. Please keep posting your questions so we can help when you are stuck.
 
Regression alone enables you to do what? a) infer causality only, b) identify correlation only c) both?
 

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