Probability over a period of time

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Discussion Overview

The discussion revolves around calculating probabilities over a period of time, specifically focusing on the probability of an event occurring over a span of 7 days. Participants explore concepts related to statistical independence and the implications of different probability values.

Discussion Character

  • Mathematical reasoning
  • Debate/contested

Main Points Raised

  • One participant inquires about finding the probability of an event happening over 7 days, given its daily probability and whether events are independent.
  • Another participant suggests that if events are independent, the probability of the event occurring at least once in 7 days can be calculated using the formula 1 - q^7, where q is the probability of the event not occurring in one day.
  • A question is raised about whether this approach derives from the union of independent events, which is challenged by another participant who states it comes from the intersection of independent events.
  • One participant expresses understanding of the logic presented in the discussion.
  • A participant presents a calculation involving probabilities of 0.1 and 0.9, questioning why their results do not add up to 1 and suggesting a potential exponential relationship based on the proximity of probabilities to 1 or 0.
  • Another participant clarifies that the calculations presented do not represent equivalent scenarios and explains that the probabilities of different outcomes do not exhaust all possibilities, thus they do not add to 1.
  • A later reply indicates a realization about the nature of the calculations, emphasizing the distinction between the probability of an event occurring versus its complement over multiple trials.

Areas of Agreement / Disagreement

Participants express differing views on the interpretation of probability calculations and the relationship between independent events. There is no consensus on the implications of the calculations presented, and the discussion remains unresolved regarding the nuances of probability theory.

Contextual Notes

Participants reference specific probability values and calculations, but there are unresolved assumptions about the nature of the events and their independence. The discussion includes potential misunderstandings about the relationship between complementary probabilities and their outcomes.

cdux
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Say I have the probability of something happening in period of a day. How am I going to tackle finding the probability of it happening in a period 7 days? Statistical independence of events or not.
 
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If they are independent it is easy. Let p = prob(event in one day), q=1-p. Then the prob of not happening in seven days is q^7, so prob happening at least once in 7 days is 1-q^7.
 
does that derive from a union of independent events?
 
cdux said:
does that derive from a union of independent events?
No. q^7 comes from the intersection of independent events.
 
Ok, I think I understand the logic now. ty.
 
mathman said:
If they are independent it is easy. Let p = prob(event in one day), q=1-p. Then the prob of not happening in seven days is q^7, so prob happening at least once in 7 days is 1-q^7.

Then how is (1-0.1)^3 = 0.729
and (1-0.9)^3 = 0.01 (only)?

(assuming an event of 0.1 (and it not happening of 0.9))

shouldn't they be equivalent? (their addition leading to 1)

EDIT: Oh, it may be I guess that the closer to 1 a probability is, the more likely to occur[in subsequent runs] in an exponential fashion, whereas the closer to 0, the less likely in a reversely exponential fashion.
 
Last edited:
I am not sure what you are trying to do. It looks like you are calculating probabilities for these two events: happening every day or never happening at all. Obviously they don't add up to 1.

Note (1-0.9)^3=0.001
 
cdux said:
Then how is (1-0.1)^3 = 0.729
and (1-0.9)^3 = 0.01 (only)?
Actually (1- 0.9)^3= 0.001.

(assuming an event of 0.1 (and it not happening of 0.9))

shouldn't they be equivalent? (their addition leading to 1)

EDIT: Oh, it may be I guess that the closer to 1 a probability is, the more likely to occur[in subsequent runs] in an exponential fashion, whereas the closer to 0, the less likely in a reversely exponential fashion.

No, they are not equivalent (and being "closer to 1" has nothing to do with it).

If you have an event that has a probability of 0.1 of "happening" in a given trial, and so a probability of 0.9 of "not happening", then (1- 0.1)^3 is the probability it does NOT happen in three consecutive trials. (1- 0.9)^3= 0.1^3 is the probability it DOES happen in all three trials. They don't add to 1 because there are many other things that could happen: happen in the first trial but not in either of second or third trials, happen on the first and third trial but not on the second trial, etc. "happen on all trials" and "happen on no trials" do not exhaust all the possible outcomes.
 
I understood what I didn't understand a while after the last post of mine.

Simply: 1-(1-"probability_of_what_we_try_to_see_IF_IT_WILL_HAPPEN in_n_subsequent runs")^n

i.e. if I put 0.01 there I try to see if that will happen in n runs. but if I put its complimentary 0.99, I'll be solving ANOTHER PROBLEM, trying to see if its complimentary will happen in n runs.
 

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