Math: Probability of Accessing CNN News from 2 Sites w/80% Reliability

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Discussion Overview

The discussion revolves around calculating the probability of accessing CNN news from two different websites, each with an 80% reliability. Participants explore how the combined reliability changes when accessing both sites compared to just one, examining different mathematical approaches to express this scenario.

Discussion Character

  • Mathematical reasoning
  • Exploratory
  • Debate/contested

Main Points Raised

  • One participant suggests that multiplying the probabilities (.8 * .8 = .64) seems incorrect since the overall probability should be greater than .8.
  • Another participant questions the setup of the scenario, asking for clarification on how the sites are accessed.
  • Some participants propose using the formula for the probability of A and/or B, indicating that at least one site working is the desired outcome.
  • A participant calculates a probability of 96% using a specific formula involving the outcomes of both sites working and not working.
  • Another participant outlines the joint outcomes of the two sites and suggests a formula for calculating the probability of at least one site working.
  • Some participants express uncertainty about how to compute the necessary probabilities, while others assert that the intuitive answer of 96% seems correct.
  • One participant simplifies the calculation by stating that the probability of not getting a feed from both sites is 0.04, leading to a probability of 0.96 for getting a feed from at least one site.
  • Another participant breaks down the probabilities of both feeds being available, only one feed being available, and neither feed being available, confirming the 96% figure.
  • A later reply introduces concepts from reliability analysis, discussing how to generalize the problem based on the configuration of the sites (series vs. parallel) and the binomial distribution.

Areas of Agreement / Disagreement

Participants express differing views on the best approach to calculate the combined probability, with some agreeing on the 96% figure while others propose different methods or express confusion about the calculations. No consensus is reached on a single method or final answer.

Contextual Notes

Some participants acknowledge potential oversights in their calculations or reasoning, and there are references to the independence of the probabilities, which may affect the outcomes. The discussion also touches on the complexity of reliability analysis without fully resolving the mathematical steps involved.

DiracPool
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How do I express the following scenario mathematically?

I have access to CNN news online from two different internet sites, each of which have about an 80% reliability of actually providing the feed when I log onto the site. If I only had access to one of the sites, I'd know that I had an 80% chance that I'd get a live feed when I logged in. How does this figure change when I have two sites, both with that 80% reliability.

The temptation is to multiply the two probabilities together, i.e., .8 * .8 = .64 But that can't be right because the probability has to be greater than .8

Can someone set this scenario up for me mathematically?
 
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If you multiply them, you're asking for the probability of getting a news feed from one site and then the other.
I think I'm missing some detail, though. So you have to choose a site, and then log in? Or what? Do both sites pop up when you log onto whatever you're logging into?
 
If that's the case, you're looking for the probability of A and/or B = A or B + A and B. At least I would think so. You only care that you get at least one, but it's also a possibility that you get two, so you need the probability of getting 1 + the probability of getting 2.
 
Ok, so this is what I'm thinking, I get a value of 96% when I do this.
##A## is getting the feed from A ##A'## is not getting the feed from A.

##P = AB' + A'B + AB##
 
Let A be the outcome "The first site works". Let B be the outcome "The second site works". Then there are 4 possible joint outcomes: A \wedge B, A \wedge \neg B, \neg A \wedge B, \neg A \wedge \neg B (where \neg means "not", and \wedge means "and"). So the probability that at least one of the sites works is:

P(A \vee B) = P(A \wedge B) + P(A \wedge \neg B) + P(\neg A \wedge B)

where \vee means "or".

So do you know how to compute those three probabilities on the right side of the equals?
 
stevendaryl said:
So do you know how to compute those three probabilities on the right side of the equals?

No I don't. But for some reason I thought intuitively the answer was what Bigyellowhat stated, 96%

BiGyElLoWhAt said:
Ok, so this is what I'm thinking, I get a value of 96% when I do this.

I don't know where I came up with that figure, and when I tried to think about how the probability would be characterized mathematically, I drew a blank. This is especially disturbing since I just took the GRE last Summer and had these type of probability questions drilled into my head. I've already forgotten how to do them :oldconfused:
 
What's the probability of A but not B?

As for where I got that number, it's the same as what Steven Darryl is doing.
 
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DiracPool said:
No I don't. But for some reason I thought intuitively the answer was what Bigyellowhat stated, 96%

You have to use some laws of probability:
P(\neg X) = 1 - P(X)
P(X \wedge Y) = P(X) \cdot P(Y) (if the probabilities are independent)
 
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stevendaryl said:
Add them up to get whatever you get.

That looks like it adds up to .96! If there's one thing I still know how to do, it's add decimals o0)

.64 + .16 + .16 =.96 Am I right? I think the probabilities are independent. If you have cable or satellite, you pretty much have a 100% reliability that you will get a CNN feed. But the two sites I get my CNN news feed from have essentially an 80% reliability independent of one another. I was just wondering how much closer to 100% my reliability was by having the two options.
 
  • #10
These answers seem somewhat over-complicated. Assuming the probabilities of NOT getting a feed from one site are independently 1 - 0.8 = 0.2, the probability of not getting a feed from both sites is 0.2 x 0.2 = 0.04. So the probability of this not happening (i.e. getting a feed from at least one site) is 1 - 0.04 = 0.96.

[edit - added this]And if you have three sites available, the probability of not getting a feed from any is 1 - 0.23 = 99.2%.
 
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  • #11
DiracPool said:
That looks like it adds up to .96! If there's one thing I still know how to do, it's add decimals o0)

.64 + .16 + .16 =.96 Am I right? I think the probabilities are independent. If you have cable or satellite, you pretty much have a 100% reliability that you will get a CNN feed. But the two sites I get my CNN news feed from have essentially an 80% reliability independent of one another. I was just wondering how much closer to 100% my reliability was by having the two options.
Yes, it's 96% if the two are independent. The simplest calculation is how often you have neither. That's 0.2 x 0.2 = 0.04.

0.8 x 0.8 = 0.64 is the probability you have both.

And 0.8 x 0.2 = 0.16 is the probability you have the first but not the second. Similarly it's the same probability you have the second but not the first. Hence:

64% both feeds available
32% only one feed available
4% neither feed available
 
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  • #12
MrAnchovy said:
These answers seem somewhat over-complicated. Assuming the probabilities of NOT getting a feed from one site are independently 1 - 0.8 = 0.2, the probability of not getting a feed from both sites is 0.2 x 0.2 = 0.04. So the probability of this not happening (i.e. getting a feed from at least one site) is 1 - 0.04 = 0.96.
I suppose I overlooked that, no? lol
 
  • #13
PeroK said:
64% both feeds available
32% only one feed available
4% neither feed available

I like how you broke that down PeroK, thanks.
 
  • #14
This is studied in reliability analysis. Basically, you have some subdevices (here: the two sites) which are operational which probability ##p##. What is asked here is what is the probability that the entire device is operational.

If the devices are connected in series, then the probability is ##p^n## where ##n## is the number of devices.
If the devices are connected in parallel, then the probability is ##1 - (1- p)^n##.
You can generalize this to ##k## out of ##n## systems where the device works if ##k## out of ##n## subdevices work. This requires the binomial distribution. Of course, you can go even more complicated than this.
 

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