Bayesian Inference: Probability of Digital Audio Device Working

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In summary, the probability that the digital audio device works on the first try is 5/12 or approximately 0.417.}\)
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An absent minded professor goes for a walk carrying a digital audio device using 2 batteries. He has 2 fresh replacement batteries stashed away in one of four pockets. Sure enough, both batteries lose their charge and he removes them. Not wanting to throw the deplete batteries into the woods, he places them into a pocket chosen at random from the 4 available. A little while later he remembers the two fresh batteries, but he cannot remember which pocket. He fishes around in his pockets until he finds one with batteries (either 2 or 4 indistinguishable batteries). He removes 2 batteries and inserts them in the digital audio device. The digital audio device requires at least one good battery in order to play.

a. Find the probability the digital audio device works on the first try. (I wasn't sure if the pocket was a variable for solving (a.) But this is how I got this answer. (1/2) - 50% chance of choosing batteries from 2 pockets, added to (1/4 * 1/3) - choosing one out of four batteries and choosing one of three batteries.

b. Given that the digital audio device plays, calculate the prob. he chose two good batteries. (I thought that the first answer would be the 'given' for this question but it doesn't seem to be the case)

c. Given that the digital audio device plays, calculate the prob. he had placed all four batteries in the same pocket.
 
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kangta27 said:
An absent minded professor goes for a walk carrying a digital audio device using 2 batteries. He has 2 fresh replacement batteries stashed away in one of four pockets. Sure enough, both batteries lose their charge and he removes them. Not wanting to throw the deplete batteries into the woods, he places them into a pocket chosen at random from the 4 available. A little while later he remembers the two fresh batteries, but he cannot remember which pocket. He fishes around in his pockets until he finds one with batteries (either 2 or 4 indistinguishable batteries). He removes 2 batteries and inserts them in the digital audio device. The digital audio device requires at least one good battery in order to play.

a. Find the probability the digital audio device works on the first try. (I wasn't sure if the pocket was a variable for solving (a.) But this is how I got this answer. (1/2) - 50% chance of choosing batteries from 2 pockets, added to (1/4 * 1/3) - choosing one out of four batteries and choosing one of three batteries.

b. Given that the digital audio device plays, calculate the prob. he chose two good batteries. (I thought that the first answer would be the 'given' for this question but it doesn't seem to be the case)

c. Given that the digital audio device plays, calculate the prob. he had placed all four batteries in the same pocket.

Lets look at a. :

\( \text{Prob(all in one pocket)=0.25}) \)

\( \text{Prob(good bad in separate pockets)=0.75)} \)

\( \text{Prob(works first time)=Prob(works first time|all in one pocket)Prob(all in one pocket) +} \)
\( \phantom{xxxxxxxxx} \text{Prob(works first time|good bad in separate pockets)Prob(good bad in separate pockets)} \)

\( \text{Prob(works first time|good bad in separate pockets)=0.5 } \)

\( \text{Prob(works first time|all in one pocket)= 5/6} \)
 

FAQ: Bayesian Inference: Probability of Digital Audio Device Working

What is Bayesian inference?

Bayesian inference is a statistical method used to update beliefs or predictions about a particular event or phenomenon, given new evidence or data. It is based on Bayes' theorem, which calculates the probability of an event happening based on prior knowledge or beliefs about that event.

How is Bayesian inference used in determining the probability of a digital audio device working?

Bayesian inference can be used to determine the probability of a digital audio device working by incorporating prior knowledge, such as the device's reliability or past performance, and new evidence, such as the device's age or maintenance history. By combining these factors, Bayesian inference can provide a more accurate estimation of the device's probability of working.

What is the difference between Bayesian inference and traditional statistical methods?

The main difference between Bayesian inference and traditional statistical methods is that Bayesian inference incorporates prior knowledge or beliefs into the analysis, while traditional methods rely solely on the data at hand. This allows Bayesian inference to provide more nuanced and accurate predictions, especially when dealing with complex or uncertain data.

Can Bayesian inference predict with 100% accuracy?

No, Bayesian inference, like any statistical method, cannot guarantee 100% accuracy in its predictions. However, by incorporating prior knowledge and updating beliefs with new evidence, Bayesian inference can provide more reliable and precise estimates compared to traditional methods.

What are some applications of Bayesian inference in other fields?

Bayesian inference has applications in various fields, including medicine, finance, and machine learning. It is used to analyze medical test results, predict stock market trends, and improve artificial intelligence algorithms, among other things. Essentially, Bayesian inference can be applied to any situation where there is uncertainty and a need to make predictions or decisions based on available data.

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